diff --git a/02_activities/assignments/assignment_1.ipynb b/02_activities/assignments/assignment_1.ipynb
index 28d4df017..91a8f3a3b 100644
--- a/02_activities/assignments/assignment_1.ipynb
+++ b/02_activities/assignments/assignment_1.ipynb
@@ -34,7 +34,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "4a3485d6-ba58-4660-a983-5680821c5719",
    "metadata": {},
    "outputs": [],
@@ -56,10 +56,288 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "a431d282-f9ca-4d5d-8912-71ffc9d8ea19",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>alcohol</th>\n",
+       "      <th>malic_acid</th>\n",
+       "      <th>ash</th>\n",
+       "      <th>alcalinity_of_ash</th>\n",
+       "      <th>magnesium</th>\n",
+       "      <th>total_phenols</th>\n",
+       "      <th>flavanoids</th>\n",
+       "      <th>nonflavanoid_phenols</th>\n",
+       "      <th>proanthocyanins</th>\n",
+       "      <th>color_intensity</th>\n",
+       "      <th>hue</th>\n",
+       "      <th>od280/od315_of_diluted_wines</th>\n",
+       "      <th>proline</th>\n",
+       "      <th>class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>14.23</td>\n",
+       "      <td>1.71</td>\n",
+       "      <td>2.43</td>\n",
+       "      <td>15.6</td>\n",
+       "      <td>127.0</td>\n",
+       "      <td>2.80</td>\n",
+       "      <td>3.06</td>\n",
+       "      <td>0.28</td>\n",
+       "      <td>2.29</td>\n",
+       "      <td>5.64</td>\n",
+       "      <td>1.04</td>\n",
+       "      <td>3.92</td>\n",
+       "      <td>1065.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>13.20</td>\n",
+       "      <td>1.78</td>\n",
+       "      <td>2.14</td>\n",
+       "      <td>11.2</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>2.65</td>\n",
+       "      <td>2.76</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>1.28</td>\n",
+       "      <td>4.38</td>\n",
+       "      <td>1.05</td>\n",
+       "      <td>3.40</td>\n",
+       "      <td>1050.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>13.16</td>\n",
+       "      <td>2.36</td>\n",
+       "      <td>2.67</td>\n",
+       "      <td>18.6</td>\n",
+       "      <td>101.0</td>\n",
+       "      <td>2.80</td>\n",
+       "      <td>3.24</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>2.81</td>\n",
+       "      <td>5.68</td>\n",
+       "      <td>1.03</td>\n",
+       "      <td>3.17</td>\n",
+       "      <td>1185.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>14.37</td>\n",
+       "      <td>1.95</td>\n",
+       "      <td>2.50</td>\n",
+       "      <td>16.8</td>\n",
+       "      <td>113.0</td>\n",
+       "      <td>3.85</td>\n",
+       "      <td>3.49</td>\n",
+       "      <td>0.24</td>\n",
+       "      <td>2.18</td>\n",
+       "      <td>7.80</td>\n",
+       "      <td>0.86</td>\n",
+       "      <td>3.45</td>\n",
+       "      <td>1480.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>13.24</td>\n",
+       "      <td>2.59</td>\n",
+       "      <td>2.87</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>118.0</td>\n",
+       "      <td>2.80</td>\n",
+       "      <td>2.69</td>\n",
+       "      <td>0.39</td>\n",
+       "      <td>1.82</td>\n",
+       "      <td>4.32</td>\n",
+       "      <td>1.04</td>\n",
+       "      <td>2.93</td>\n",
+       "      <td>735.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>173</th>\n",
+       "      <td>13.71</td>\n",
+       "      <td>5.65</td>\n",
+       "      <td>2.45</td>\n",
+       "      <td>20.5</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>1.68</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>0.52</td>\n",
+       "      <td>1.06</td>\n",
+       "      <td>7.70</td>\n",
+       "      <td>0.64</td>\n",
+       "      <td>1.74</td>\n",
+       "      <td>740.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>174</th>\n",
+       "      <td>13.40</td>\n",
+       "      <td>3.91</td>\n",
+       "      <td>2.48</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>102.0</td>\n",
+       "      <td>1.80</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>0.43</td>\n",
+       "      <td>1.41</td>\n",
+       "      <td>7.30</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>750.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>175</th>\n",
+       "      <td>13.27</td>\n",
+       "      <td>4.28</td>\n",
+       "      <td>2.26</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>1.59</td>\n",
+       "      <td>0.69</td>\n",
+       "      <td>0.43</td>\n",
+       "      <td>1.35</td>\n",
+       "      <td>10.20</td>\n",
+       "      <td>0.59</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>835.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>176</th>\n",
+       "      <td>13.17</td>\n",
+       "      <td>2.59</td>\n",
+       "      <td>2.37</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>1.65</td>\n",
+       "      <td>0.68</td>\n",
+       "      <td>0.53</td>\n",
+       "      <td>1.46</td>\n",
+       "      <td>9.30</td>\n",
+       "      <td>0.60</td>\n",
+       "      <td>1.62</td>\n",
+       "      <td>840.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>177</th>\n",
+       "      <td>14.13</td>\n",
+       "      <td>4.10</td>\n",
+       "      <td>2.74</td>\n",
+       "      <td>24.5</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>2.05</td>\n",
+       "      <td>0.76</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>1.35</td>\n",
+       "      <td>9.20</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>1.60</td>\n",
+       "      <td>560.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>178 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     alcohol  malic_acid   ash  alcalinity_of_ash  magnesium  total_phenols  \\\n",
+       "0      14.23        1.71  2.43               15.6      127.0           2.80   \n",
+       "1      13.20        1.78  2.14               11.2      100.0           2.65   \n",
+       "2      13.16        2.36  2.67               18.6      101.0           2.80   \n",
+       "3      14.37        1.95  2.50               16.8      113.0           3.85   \n",
+       "4      13.24        2.59  2.87               21.0      118.0           2.80   \n",
+       "..       ...         ...   ...                ...        ...            ...   \n",
+       "173    13.71        5.65  2.45               20.5       95.0           1.68   \n",
+       "174    13.40        3.91  2.48               23.0      102.0           1.80   \n",
+       "175    13.27        4.28  2.26               20.0      120.0           1.59   \n",
+       "176    13.17        2.59  2.37               20.0      120.0           1.65   \n",
+       "177    14.13        4.10  2.74               24.5       96.0           2.05   \n",
+       "\n",
+       "     flavanoids  nonflavanoid_phenols  proanthocyanins  color_intensity   hue  \\\n",
+       "0          3.06                  0.28             2.29             5.64  1.04   \n",
+       "1          2.76                  0.26             1.28             4.38  1.05   \n",
+       "2          3.24                  0.30             2.81             5.68  1.03   \n",
+       "3          3.49                  0.24             2.18             7.80  0.86   \n",
+       "4          2.69                  0.39             1.82             4.32  1.04   \n",
+       "..          ...                   ...              ...              ...   ...   \n",
+       "173        0.61                  0.52             1.06             7.70  0.64   \n",
+       "174        0.75                  0.43             1.41             7.30  0.70   \n",
+       "175        0.69                  0.43             1.35            10.20  0.59   \n",
+       "176        0.68                  0.53             1.46             9.30  0.60   \n",
+       "177        0.76                  0.56             1.35             9.20  0.61   \n",
+       "\n",
+       "     od280/od315_of_diluted_wines  proline  class  \n",
+       "0                            3.92   1065.0      0  \n",
+       "1                            3.40   1050.0      0  \n",
+       "2                            3.17   1185.0      0  \n",
+       "3                            3.45   1480.0      0  \n",
+       "4                            2.93    735.0      0  \n",
+       "..                            ...      ...    ...  \n",
+       "173                          1.74    740.0      2  \n",
+       "174                          1.56    750.0      2  \n",
+       "175                          1.56    835.0      2  \n",
+       "176                          1.62    840.0      2  \n",
+       "177                          1.60    560.0      2  \n",
+       "\n",
+       "[178 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "from sklearn.datasets import load_wine\n",
     "\n",
@@ -91,12 +369,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "56916892",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "178"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your answer here"
+    "178"
    ]
   },
   {
@@ -109,12 +398,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "df0ef103",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "14"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your answer here"
+    "14\n"
    ]
   },
   {
@@ -127,12 +427,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "47989426",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0, 1, 2])"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your answer here"
+    " wine_df['class'].unique()\n",
+    "\n"
    ]
   },
   {
@@ -146,12 +458,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "bd7b0910",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "13"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your answer here"
+    "13"
    ]
   },
   {
@@ -175,20 +498,306 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "cc899b59",
+   "execution_count": 7,
+   "id": "f304cef6",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>alcohol</th>\n",
+       "      <th>malic_acid</th>\n",
+       "      <th>ash</th>\n",
+       "      <th>alcalinity_of_ash</th>\n",
+       "      <th>magnesium</th>\n",
+       "      <th>total_phenols</th>\n",
+       "      <th>flavanoids</th>\n",
+       "      <th>nonflavanoid_phenols</th>\n",
+       "      <th>proanthocyanins</th>\n",
+       "      <th>color_intensity</th>\n",
+       "      <th>hue</th>\n",
+       "      <th>od280/od315_of_diluted_wines</th>\n",
+       "      <th>proline</th>\n",
+       "      <th>class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1.518613</td>\n",
+       "      <td>-0.562250</td>\n",
+       "      <td>0.232053</td>\n",
+       "      <td>-1.169593</td>\n",
+       "      <td>1.913905</td>\n",
+       "      <td>0.808997</td>\n",
+       "      <td>1.034819</td>\n",
+       "      <td>-0.659563</td>\n",
+       "      <td>1.224884</td>\n",
+       "      <td>0.251717</td>\n",
+       "      <td>0.362177</td>\n",
+       "      <td>1.847920</td>\n",
+       "      <td>1.013009</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.246290</td>\n",
+       "      <td>-0.499413</td>\n",
+       "      <td>-0.827996</td>\n",
+       "      <td>-2.490847</td>\n",
+       "      <td>0.018145</td>\n",
+       "      <td>0.568648</td>\n",
+       "      <td>0.733629</td>\n",
+       "      <td>-0.820719</td>\n",
+       "      <td>-0.544721</td>\n",
+       "      <td>-0.293321</td>\n",
+       "      <td>0.406051</td>\n",
+       "      <td>1.113449</td>\n",
+       "      <td>0.965242</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.196879</td>\n",
+       "      <td>0.021231</td>\n",
+       "      <td>1.109334</td>\n",
+       "      <td>-0.268738</td>\n",
+       "      <td>0.088358</td>\n",
+       "      <td>0.808997</td>\n",
+       "      <td>1.215533</td>\n",
+       "      <td>-0.498407</td>\n",
+       "      <td>2.135968</td>\n",
+       "      <td>0.269020</td>\n",
+       "      <td>0.318304</td>\n",
+       "      <td>0.788587</td>\n",
+       "      <td>1.395148</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1.691550</td>\n",
+       "      <td>-0.346811</td>\n",
+       "      <td>0.487926</td>\n",
+       "      <td>-0.809251</td>\n",
+       "      <td>0.930918</td>\n",
+       "      <td>2.491446</td>\n",
+       "      <td>1.466525</td>\n",
+       "      <td>-0.981875</td>\n",
+       "      <td>1.032155</td>\n",
+       "      <td>1.186068</td>\n",
+       "      <td>-0.427544</td>\n",
+       "      <td>1.184071</td>\n",
+       "      <td>2.334574</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.295700</td>\n",
+       "      <td>0.227694</td>\n",
+       "      <td>1.840403</td>\n",
+       "      <td>0.451946</td>\n",
+       "      <td>1.281985</td>\n",
+       "      <td>0.808997</td>\n",
+       "      <td>0.663351</td>\n",
+       "      <td>0.226796</td>\n",
+       "      <td>0.401404</td>\n",
+       "      <td>-0.319276</td>\n",
+       "      <td>0.362177</td>\n",
+       "      <td>0.449601</td>\n",
+       "      <td>-0.037874</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>173</th>\n",
+       "      <td>0.876275</td>\n",
+       "      <td>2.974543</td>\n",
+       "      <td>0.305159</td>\n",
+       "      <td>0.301803</td>\n",
+       "      <td>-0.332922</td>\n",
+       "      <td>-0.985614</td>\n",
+       "      <td>-1.424900</td>\n",
+       "      <td>1.274310</td>\n",
+       "      <td>-0.930179</td>\n",
+       "      <td>1.142811</td>\n",
+       "      <td>-1.392758</td>\n",
+       "      <td>-1.231206</td>\n",
+       "      <td>-0.021952</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>174</th>\n",
+       "      <td>0.493343</td>\n",
+       "      <td>1.412609</td>\n",
+       "      <td>0.414820</td>\n",
+       "      <td>1.052516</td>\n",
+       "      <td>0.158572</td>\n",
+       "      <td>-0.793334</td>\n",
+       "      <td>-1.284344</td>\n",
+       "      <td>0.549108</td>\n",
+       "      <td>-0.316950</td>\n",
+       "      <td>0.969783</td>\n",
+       "      <td>-1.129518</td>\n",
+       "      <td>-1.485445</td>\n",
+       "      <td>0.009893</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>175</th>\n",
+       "      <td>0.332758</td>\n",
+       "      <td>1.744744</td>\n",
+       "      <td>-0.389355</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>1.422412</td>\n",
+       "      <td>-1.129824</td>\n",
+       "      <td>-1.344582</td>\n",
+       "      <td>0.549108</td>\n",
+       "      <td>-0.422075</td>\n",
+       "      <td>2.224236</td>\n",
+       "      <td>-1.612125</td>\n",
+       "      <td>-1.485445</td>\n",
+       "      <td>0.280575</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>176</th>\n",
+       "      <td>0.209232</td>\n",
+       "      <td>0.227694</td>\n",
+       "      <td>0.012732</td>\n",
+       "      <td>0.151661</td>\n",
+       "      <td>1.422412</td>\n",
+       "      <td>-1.033684</td>\n",
+       "      <td>-1.354622</td>\n",
+       "      <td>1.354888</td>\n",
+       "      <td>-0.229346</td>\n",
+       "      <td>1.834923</td>\n",
+       "      <td>-1.568252</td>\n",
+       "      <td>-1.400699</td>\n",
+       "      <td>0.296498</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>177</th>\n",
+       "      <td>1.395086</td>\n",
+       "      <td>1.583165</td>\n",
+       "      <td>1.365208</td>\n",
+       "      <td>1.502943</td>\n",
+       "      <td>-0.262708</td>\n",
+       "      <td>-0.392751</td>\n",
+       "      <td>-1.274305</td>\n",
+       "      <td>1.596623</td>\n",
+       "      <td>-0.422075</td>\n",
+       "      <td>1.791666</td>\n",
+       "      <td>-1.524378</td>\n",
+       "      <td>-1.428948</td>\n",
+       "      <td>-0.595160</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>178 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      alcohol  malic_acid       ash  alcalinity_of_ash  magnesium  \\\n",
+       "0    1.518613   -0.562250  0.232053          -1.169593   1.913905   \n",
+       "1    0.246290   -0.499413 -0.827996          -2.490847   0.018145   \n",
+       "2    0.196879    0.021231  1.109334          -0.268738   0.088358   \n",
+       "3    1.691550   -0.346811  0.487926          -0.809251   0.930918   \n",
+       "4    0.295700    0.227694  1.840403           0.451946   1.281985   \n",
+       "..        ...         ...       ...                ...        ...   \n",
+       "173  0.876275    2.974543  0.305159           0.301803  -0.332922   \n",
+       "174  0.493343    1.412609  0.414820           1.052516   0.158572   \n",
+       "175  0.332758    1.744744 -0.389355           0.151661   1.422412   \n",
+       "176  0.209232    0.227694  0.012732           0.151661   1.422412   \n",
+       "177  1.395086    1.583165  1.365208           1.502943  -0.262708   \n",
+       "\n",
+       "     total_phenols  flavanoids  nonflavanoid_phenols  proanthocyanins  \\\n",
+       "0         0.808997    1.034819             -0.659563         1.224884   \n",
+       "1         0.568648    0.733629             -0.820719        -0.544721   \n",
+       "2         0.808997    1.215533             -0.498407         2.135968   \n",
+       "3         2.491446    1.466525             -0.981875         1.032155   \n",
+       "4         0.808997    0.663351              0.226796         0.401404   \n",
+       "..             ...         ...                   ...              ...   \n",
+       "173      -0.985614   -1.424900              1.274310        -0.930179   \n",
+       "174      -0.793334   -1.284344              0.549108        -0.316950   \n",
+       "175      -1.129824   -1.344582              0.549108        -0.422075   \n",
+       "176      -1.033684   -1.354622              1.354888        -0.229346   \n",
+       "177      -0.392751   -1.274305              1.596623        -0.422075   \n",
+       "\n",
+       "     color_intensity       hue  od280/od315_of_diluted_wines   proline  class  \n",
+       "0           0.251717  0.362177                      1.847920  1.013009      0  \n",
+       "1          -0.293321  0.406051                      1.113449  0.965242      0  \n",
+       "2           0.269020  0.318304                      0.788587  1.395148      0  \n",
+       "3           1.186068 -0.427544                      1.184071  2.334574      0  \n",
+       "4          -0.319276  0.362177                      0.449601 -0.037874      0  \n",
+       "..               ...       ...                           ...       ...    ...  \n",
+       "173         1.142811 -1.392758                     -1.231206 -0.021952      2  \n",
+       "174         0.969783 -1.129518                     -1.485445  0.009893      2  \n",
+       "175         2.224236 -1.612125                     -1.485445  0.280575      2  \n",
+       "176         1.834923 -1.568252                     -1.400699  0.296498      2  \n",
+       "177         1.791666 -1.524378                     -1.428948 -0.595160      2  \n",
+       "\n",
+       "[178 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Select predictors (excluding the last column)\n",
-    "predictors = wine_df.iloc[:, :-1]\n",
+    "predictors_standardized = wine_df.copy()\n",
+    "columns_to_exclude = ['class']\n",
     "\n",
-    "# Standardize the predictors\n",
+    "# Select the columns that we want to scale by excluding the 'id' and 'diagnosis' columns\n",
+    "# This will return a list of the numeric columns we need to scale\n",
+    "columns_to_scale = predictors_standardized.columns.difference(columns_to_exclude)\n",
+    "\n",
+    "# Initialize the StandardScaler to standardize the selected numeric columns\n",
     "scaler = StandardScaler()\n",
-    "predictors_standardized = pd.DataFrame(scaler.fit_transform(predictors), columns=predictors.columns)\n",
     "\n",
-    "# Display the head of the standardized predictors\n",
-    "print(predictors_standardized.head())"
+    "# Apply the scaler to the selected columns. This transforms the data so that each feature\n",
+    "# has a mean of 0 and a standard deviation of 1, which is essential to prevent larger\n",
+    "# scale features from dominating the analysis, especially for distance-based algorithms like KNN.\n",
+    "predictors_standardized[columns_to_scale] = scaler.fit_transform(wine_df[columns_to_scale])\n",
+    "\n",
+    "# Output the standardized dataframe with the scaled numeric columns\n",
+    "predictors_standardized"
    ]
   },
   {
@@ -204,7 +813,7 @@
    "id": "403ef0bb",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "Standardizing predictor variables allows models to treat each predictor fairly and making the coefficients easier to compare. Without standardization, predictors measured in large units can dominate the calculation and lead to unstable or less reliable model estimates. Standardizing also improves the numerical stability of the regression algorithm and is essential when using regularization methods like Ridge or Lasso, which penalize coefficients based on their size. "
    ]
   },
   {
@@ -220,7 +829,7 @@
    "id": "fdee5a15",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "The 'class' variable in this case is a categorical variable, despite being a string. Standardization only makes sense for continous veriables where the differences and sitances have meaningful interpreations. In the case of categorical data, it represents groupings of the data opposed to specific numerical values. "
    ]
   },
   {
@@ -236,7 +845,7 @@
    "id": "f0676c21",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "The specific seed value is not important, but rather setting the seed function, as it ensures that the data is randomly split between the training and testing data and ensures reproducibility in the data. "
    ]
   },
   {
@@ -251,7 +860,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "72c101f2",
    "metadata": {},
    "outputs": [],
@@ -261,7 +870,10 @@
     "\n",
     "# split the data into a training and testing set. hint: use train_test_split !\n",
     "\n",
-    "# Your code here ..."
+    "wine_train, wine_test = train_test_split(\n",
+    "    predictors_standardized, train_size=0.75, stratify=predictors_standardized[\"class\"]\n",
+    ")\n",
+    "\n"
    ]
   },
   {
@@ -284,12 +896,1496 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "id": "08818c64",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>mean_fit_time</th>\n",
+       "      <th>std_fit_time</th>\n",
+       "      <th>mean_score_time</th>\n",
+       "      <th>std_score_time</th>\n",
+       "      <th>param_n_neighbors</th>\n",
+       "      <th>params</th>\n",
+       "      <th>split0_test_score</th>\n",
+       "      <th>split1_test_score</th>\n",
+       "      <th>split2_test_score</th>\n",
+       "      <th>split3_test_score</th>\n",
+       "      <th>split4_test_score</th>\n",
+       "      <th>split5_test_score</th>\n",
+       "      <th>split6_test_score</th>\n",
+       "      <th>split7_test_score</th>\n",
+       "      <th>split8_test_score</th>\n",
+       "      <th>split9_test_score</th>\n",
+       "      <th>mean_test_score</th>\n",
+       "      <th>std_test_score</th>\n",
+       "      <th>rank_test_score</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.005224</td>\n",
+       "      <td>0.011857</td>\n",
+       "      <td>0.004419</td>\n",
+       "      <td>0.008788</td>\n",
+       "      <td>1</td>\n",
+       "      <td>{'n_neighbors': 1}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.692308</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954396</td>\n",
+       "      <td>0.092139</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.000935</td>\n",
+       "      <td>0.000028</td>\n",
+       "      <td>0.001249</td>\n",
+       "      <td>0.000068</td>\n",
+       "      <td>2</td>\n",
+       "      <td>{'n_neighbors': 2}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.692308</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.939011</td>\n",
+       "      <td>0.089628</td>\n",
+       "      <td>50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.001057</td>\n",
+       "      <td>0.000247</td>\n",
+       "      <td>0.001277</td>\n",
+       "      <td>0.000061</td>\n",
+       "      <td>3</td>\n",
+       "      <td>{'n_neighbors': 3}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.962088</td>\n",
+       "      <td>0.051217</td>\n",
+       "      <td>28</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.001061</td>\n",
+       "      <td>0.000187</td>\n",
+       "      <td>0.004589</td>\n",
+       "      <td>0.009698</td>\n",
+       "      <td>4</td>\n",
+       "      <td>{'n_neighbors': 4}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.050406</td>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.001042</td>\n",
+       "      <td>0.000106</td>\n",
+       "      <td>0.065221</td>\n",
+       "      <td>0.191469</td>\n",
+       "      <td>5</td>\n",
+       "      <td>{'n_neighbors': 5}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.969780</td>\n",
+       "      <td>0.037042</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>0.001389</td>\n",
+       "      <td>0.000854</td>\n",
+       "      <td>0.001617</td>\n",
+       "      <td>0.000422</td>\n",
+       "      <td>6</td>\n",
+       "      <td>{'n_neighbors': 6}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.969780</td>\n",
+       "      <td>0.037042</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>0.000990</td>\n",
+       "      <td>0.000061</td>\n",
+       "      <td>0.001286</td>\n",
+       "      <td>0.000058</td>\n",
+       "      <td>7</td>\n",
+       "      <td>{'n_neighbors': 7}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.977473</td>\n",
+       "      <td>0.034441</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0.000989</td>\n",
+       "      <td>0.000045</td>\n",
+       "      <td>0.001357</td>\n",
+       "      <td>0.000100</td>\n",
+       "      <td>8</td>\n",
+       "      <td>{'n_neighbors': 8}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.954396</td>\n",
+       "      <td>0.050719</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>0.000980</td>\n",
+       "      <td>0.000053</td>\n",
+       "      <td>0.001340</td>\n",
+       "      <td>0.000133</td>\n",
+       "      <td>9</td>\n",
+       "      <td>{'n_neighbors': 9}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.969780</td>\n",
+       "      <td>0.037042</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>0.000955</td>\n",
+       "      <td>0.000062</td>\n",
+       "      <td>0.001259</td>\n",
+       "      <td>0.000055</td>\n",
+       "      <td>10</td>\n",
+       "      <td>{'n_neighbors': 10}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.954396</td>\n",
+       "      <td>0.050719</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>0.000946</td>\n",
+       "      <td>0.000052</td>\n",
+       "      <td>0.001251</td>\n",
+       "      <td>0.000038</td>\n",
+       "      <td>11</td>\n",
+       "      <td>{'n_neighbors': 11}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>0.000955</td>\n",
+       "      <td>0.000026</td>\n",
+       "      <td>0.001298</td>\n",
+       "      <td>0.000100</td>\n",
+       "      <td>12</td>\n",
+       "      <td>{'n_neighbors': 12}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.969780</td>\n",
+       "      <td>0.037042</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>0.000968</td>\n",
+       "      <td>0.000065</td>\n",
+       "      <td>0.001286</td>\n",
+       "      <td>0.000055</td>\n",
+       "      <td>13</td>\n",
+       "      <td>{'n_neighbors': 13}</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.977473</td>\n",
+       "      <td>0.034441</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>0.000925</td>\n",
+       "      <td>0.000013</td>\n",
+       "      <td>0.001242</td>\n",
+       "      <td>0.000036</td>\n",
+       "      <td>14</td>\n",
+       "      <td>{'n_neighbors': 14}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>0.000928</td>\n",
+       "      <td>0.000016</td>\n",
+       "      <td>0.001248</td>\n",
+       "      <td>0.000033</td>\n",
+       "      <td>15</td>\n",
+       "      <td>{'n_neighbors': 15}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>0.000961</td>\n",
+       "      <td>0.000048</td>\n",
+       "      <td>0.001285</td>\n",
+       "      <td>0.000048</td>\n",
+       "      <td>16</td>\n",
+       "      <td>{'n_neighbors': 16}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>0.000958</td>\n",
+       "      <td>0.000057</td>\n",
+       "      <td>0.001273</td>\n",
+       "      <td>0.000034</td>\n",
+       "      <td>17</td>\n",
+       "      <td>{'n_neighbors': 17}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>0.000952</td>\n",
+       "      <td>0.000039</td>\n",
+       "      <td>0.001301</td>\n",
+       "      <td>0.000047</td>\n",
+       "      <td>18</td>\n",
+       "      <td>{'n_neighbors': 18}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>0.000949</td>\n",
+       "      <td>0.000035</td>\n",
+       "      <td>0.001289</td>\n",
+       "      <td>0.000072</td>\n",
+       "      <td>19</td>\n",
+       "      <td>{'n_neighbors': 19}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>0.000928</td>\n",
+       "      <td>0.000011</td>\n",
+       "      <td>0.001271</td>\n",
+       "      <td>0.000035</td>\n",
+       "      <td>20</td>\n",
+       "      <td>{'n_neighbors': 20}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.963187</td>\n",
+       "      <td>0.048777</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>0.000953</td>\n",
+       "      <td>0.000036</td>\n",
+       "      <td>0.001307</td>\n",
+       "      <td>0.000088</td>\n",
+       "      <td>21</td>\n",
+       "      <td>{'n_neighbors': 21}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.970330</td>\n",
+       "      <td>0.036380</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>0.000949</td>\n",
+       "      <td>0.000030</td>\n",
+       "      <td>0.001272</td>\n",
+       "      <td>0.000024</td>\n",
+       "      <td>22</td>\n",
+       "      <td>{'n_neighbors': 22}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.970330</td>\n",
+       "      <td>0.036380</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>0.000986</td>\n",
+       "      <td>0.000082</td>\n",
+       "      <td>0.001289</td>\n",
+       "      <td>0.000047</td>\n",
+       "      <td>23</td>\n",
+       "      <td>{'n_neighbors': 23}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>0.000939</td>\n",
+       "      <td>0.000012</td>\n",
+       "      <td>0.001285</td>\n",
+       "      <td>0.000032</td>\n",
+       "      <td>24</td>\n",
+       "      <td>{'n_neighbors': 24}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.970330</td>\n",
+       "      <td>0.036380</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>0.000949</td>\n",
+       "      <td>0.000034</td>\n",
+       "      <td>0.001290</td>\n",
+       "      <td>0.000041</td>\n",
+       "      <td>25</td>\n",
+       "      <td>{'n_neighbors': 25}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.050406</td>\n",
+       "      <td>33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>0.000933</td>\n",
+       "      <td>0.000019</td>\n",
+       "      <td>0.001281</td>\n",
+       "      <td>0.000029</td>\n",
+       "      <td>26</td>\n",
+       "      <td>{'n_neighbors': 26}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.050823</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>0.000948</td>\n",
+       "      <td>0.000032</td>\n",
+       "      <td>0.001322</td>\n",
+       "      <td>0.000075</td>\n",
+       "      <td>27</td>\n",
+       "      <td>{'n_neighbors': 27}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.050406</td>\n",
+       "      <td>33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>0.000928</td>\n",
+       "      <td>0.000012</td>\n",
+       "      <td>0.001278</td>\n",
+       "      <td>0.000043</td>\n",
+       "      <td>28</td>\n",
+       "      <td>{'n_neighbors': 28}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>0.000939</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.001290</td>\n",
+       "      <td>0.000046</td>\n",
+       "      <td>29</td>\n",
+       "      <td>{'n_neighbors': 29}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>0.000957</td>\n",
+       "      <td>0.000036</td>\n",
+       "      <td>0.001320</td>\n",
+       "      <td>0.000063</td>\n",
+       "      <td>30</td>\n",
+       "      <td>{'n_neighbors': 30}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947802</td>\n",
+       "      <td>0.046832</td>\n",
+       "      <td>42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>0.000965</td>\n",
+       "      <td>0.000074</td>\n",
+       "      <td>0.001310</td>\n",
+       "      <td>0.000049</td>\n",
+       "      <td>31</td>\n",
+       "      <td>{'n_neighbors': 31}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.955495</td>\n",
+       "      <td>0.048430</td>\n",
+       "      <td>29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>0.000927</td>\n",
+       "      <td>0.000007</td>\n",
+       "      <td>0.001263</td>\n",
+       "      <td>0.000013</td>\n",
+       "      <td>32</td>\n",
+       "      <td>{'n_neighbors': 32}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.955495</td>\n",
+       "      <td>0.048430</td>\n",
+       "      <td>29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>0.000924</td>\n",
+       "      <td>0.000018</td>\n",
+       "      <td>0.001283</td>\n",
+       "      <td>0.000030</td>\n",
+       "      <td>33</td>\n",
+       "      <td>{'n_neighbors': 33}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.955495</td>\n",
+       "      <td>0.048430</td>\n",
+       "      <td>29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>0.000947</td>\n",
+       "      <td>0.000043</td>\n",
+       "      <td>0.001361</td>\n",
+       "      <td>0.000124</td>\n",
+       "      <td>34</td>\n",
+       "      <td>{'n_neighbors': 34}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.963187</td>\n",
+       "      <td>0.048777</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>0.000929</td>\n",
+       "      <td>0.000005</td>\n",
+       "      <td>0.001264</td>\n",
+       "      <td>0.000010</td>\n",
+       "      <td>35</td>\n",
+       "      <td>{'n_neighbors': 35}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.955495</td>\n",
+       "      <td>0.048430</td>\n",
+       "      <td>29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>0.000961</td>\n",
+       "      <td>0.000031</td>\n",
+       "      <td>0.001339</td>\n",
+       "      <td>0.000052</td>\n",
+       "      <td>36</td>\n",
+       "      <td>{'n_neighbors': 36}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>0.000980</td>\n",
+       "      <td>0.000140</td>\n",
+       "      <td>0.001291</td>\n",
+       "      <td>0.000027</td>\n",
+       "      <td>37</td>\n",
+       "      <td>{'n_neighbors': 37}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>0.000963</td>\n",
+       "      <td>0.000064</td>\n",
+       "      <td>0.001307</td>\n",
+       "      <td>0.000044</td>\n",
+       "      <td>38</td>\n",
+       "      <td>{'n_neighbors': 38}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>0.000953</td>\n",
+       "      <td>0.000053</td>\n",
+       "      <td>0.001313</td>\n",
+       "      <td>0.000039</td>\n",
+       "      <td>39</td>\n",
+       "      <td>{'n_neighbors': 39}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.962637</td>\n",
+       "      <td>0.037411</td>\n",
+       "      <td>17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>0.000933</td>\n",
+       "      <td>0.000011</td>\n",
+       "      <td>0.001312</td>\n",
+       "      <td>0.000047</td>\n",
+       "      <td>40</td>\n",
+       "      <td>{'n_neighbors': 40}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.036842</td>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>0.000951</td>\n",
+       "      <td>0.000034</td>\n",
+       "      <td>0.001359</td>\n",
+       "      <td>0.000145</td>\n",
+       "      <td>41</td>\n",
+       "      <td>{'n_neighbors': 41}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.970330</td>\n",
+       "      <td>0.036380</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>0.000932</td>\n",
+       "      <td>0.000019</td>\n",
+       "      <td>0.001297</td>\n",
+       "      <td>0.000029</td>\n",
+       "      <td>42</td>\n",
+       "      <td>{'n_neighbors': 42}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.036842</td>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>0.000951</td>\n",
+       "      <td>0.000048</td>\n",
+       "      <td>0.001315</td>\n",
+       "      <td>0.000038</td>\n",
+       "      <td>43</td>\n",
+       "      <td>{'n_neighbors': 43}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.954945</td>\n",
+       "      <td>0.036842</td>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>0.000938</td>\n",
+       "      <td>0.000012</td>\n",
+       "      <td>0.001317</td>\n",
+       "      <td>0.000051</td>\n",
+       "      <td>44</td>\n",
+       "      <td>{'n_neighbors': 44}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.048787</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>0.000967</td>\n",
+       "      <td>0.000052</td>\n",
+       "      <td>0.001344</td>\n",
+       "      <td>0.000050</td>\n",
+       "      <td>45</td>\n",
+       "      <td>{'n_neighbors': 45}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.048787</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>0.000949</td>\n",
+       "      <td>0.000049</td>\n",
+       "      <td>0.001295</td>\n",
+       "      <td>0.000013</td>\n",
+       "      <td>46</td>\n",
+       "      <td>{'n_neighbors': 46}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.846154</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.048787</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>0.000962</td>\n",
+       "      <td>0.000050</td>\n",
+       "      <td>0.001330</td>\n",
+       "      <td>0.000042</td>\n",
+       "      <td>47</td>\n",
+       "      <td>{'n_neighbors': 47}</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947802</td>\n",
+       "      <td>0.046832</td>\n",
+       "      <td>42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>0.000936</td>\n",
+       "      <td>0.000012</td>\n",
+       "      <td>0.001297</td>\n",
+       "      <td>0.000018</td>\n",
+       "      <td>48</td>\n",
+       "      <td>{'n_neighbors': 48}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.034594</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>0.000946</td>\n",
+       "      <td>0.000010</td>\n",
+       "      <td>0.001327</td>\n",
+       "      <td>0.000045</td>\n",
+       "      <td>49</td>\n",
+       "      <td>{'n_neighbors': 49}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.034594</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>0.000932</td>\n",
+       "      <td>0.000011</td>\n",
+       "      <td>0.001293</td>\n",
+       "      <td>0.000015</td>\n",
+       "      <td>50</td>\n",
+       "      <td>{'n_neighbors': 50}</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>0.928571</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.923077</td>\n",
+       "      <td>0.947253</td>\n",
+       "      <td>0.034594</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    mean_fit_time  std_fit_time  mean_score_time  std_score_time  \\\n",
+       "0        0.005224      0.011857         0.004419        0.008788   \n",
+       "1        0.000935      0.000028         0.001249        0.000068   \n",
+       "2        0.001057      0.000247         0.001277        0.000061   \n",
+       "3        0.001061      0.000187         0.004589        0.009698   \n",
+       "4        0.001042      0.000106         0.065221        0.191469   \n",
+       "5        0.001389      0.000854         0.001617        0.000422   \n",
+       "6        0.000990      0.000061         0.001286        0.000058   \n",
+       "7        0.000989      0.000045         0.001357        0.000100   \n",
+       "8        0.000980      0.000053         0.001340        0.000133   \n",
+       "9        0.000955      0.000062         0.001259        0.000055   \n",
+       "10       0.000946      0.000052         0.001251        0.000038   \n",
+       "11       0.000955      0.000026         0.001298        0.000100   \n",
+       "12       0.000968      0.000065         0.001286        0.000055   \n",
+       "13       0.000925      0.000013         0.001242        0.000036   \n",
+       "14       0.000928      0.000016         0.001248        0.000033   \n",
+       "15       0.000961      0.000048         0.001285        0.000048   \n",
+       "16       0.000958      0.000057         0.001273        0.000034   \n",
+       "17       0.000952      0.000039         0.001301        0.000047   \n",
+       "18       0.000949      0.000035         0.001289        0.000072   \n",
+       "19       0.000928      0.000011         0.001271        0.000035   \n",
+       "20       0.000953      0.000036         0.001307        0.000088   \n",
+       "21       0.000949      0.000030         0.001272        0.000024   \n",
+       "22       0.000986      0.000082         0.001289        0.000047   \n",
+       "23       0.000939      0.000012         0.001285        0.000032   \n",
+       "24       0.000949      0.000034         0.001290        0.000041   \n",
+       "25       0.000933      0.000019         0.001281        0.000029   \n",
+       "26       0.000948      0.000032         0.001322        0.000075   \n",
+       "27       0.000928      0.000012         0.001278        0.000043   \n",
+       "28       0.000939      0.000017         0.001290        0.000046   \n",
+       "29       0.000957      0.000036         0.001320        0.000063   \n",
+       "30       0.000965      0.000074         0.001310        0.000049   \n",
+       "31       0.000927      0.000007         0.001263        0.000013   \n",
+       "32       0.000924      0.000018         0.001283        0.000030   \n",
+       "33       0.000947      0.000043         0.001361        0.000124   \n",
+       "34       0.000929      0.000005         0.001264        0.000010   \n",
+       "35       0.000961      0.000031         0.001339        0.000052   \n",
+       "36       0.000980      0.000140         0.001291        0.000027   \n",
+       "37       0.000963      0.000064         0.001307        0.000044   \n",
+       "38       0.000953      0.000053         0.001313        0.000039   \n",
+       "39       0.000933      0.000011         0.001312        0.000047   \n",
+       "40       0.000951      0.000034         0.001359        0.000145   \n",
+       "41       0.000932      0.000019         0.001297        0.000029   \n",
+       "42       0.000951      0.000048         0.001315        0.000038   \n",
+       "43       0.000938      0.000012         0.001317        0.000051   \n",
+       "44       0.000967      0.000052         0.001344        0.000050   \n",
+       "45       0.000949      0.000049         0.001295        0.000013   \n",
+       "46       0.000962      0.000050         0.001330        0.000042   \n",
+       "47       0.000936      0.000012         0.001297        0.000018   \n",
+       "48       0.000946      0.000010         0.001327        0.000045   \n",
+       "49       0.000932      0.000011         0.001293        0.000015   \n",
+       "\n",
+       "    param_n_neighbors               params  split0_test_score  \\\n",
+       "0                   1   {'n_neighbors': 1}           1.000000   \n",
+       "1                   2   {'n_neighbors': 2}           1.000000   \n",
+       "2                   3   {'n_neighbors': 3}           1.000000   \n",
+       "3                   4   {'n_neighbors': 4}           0.928571   \n",
+       "4                   5   {'n_neighbors': 5}           1.000000   \n",
+       "5                   6   {'n_neighbors': 6}           0.928571   \n",
+       "6                   7   {'n_neighbors': 7}           1.000000   \n",
+       "7                   8   {'n_neighbors': 8}           0.928571   \n",
+       "8                   9   {'n_neighbors': 9}           1.000000   \n",
+       "9                  10  {'n_neighbors': 10}           1.000000   \n",
+       "10                 11  {'n_neighbors': 11}           0.928571   \n",
+       "11                 12  {'n_neighbors': 12}           1.000000   \n",
+       "12                 13  {'n_neighbors': 13}           1.000000   \n",
+       "13                 14  {'n_neighbors': 14}           0.928571   \n",
+       "14                 15  {'n_neighbors': 15}           0.928571   \n",
+       "15                 16  {'n_neighbors': 16}           0.928571   \n",
+       "16                 17  {'n_neighbors': 17}           0.928571   \n",
+       "17                 18  {'n_neighbors': 18}           0.928571   \n",
+       "18                 19  {'n_neighbors': 19}           0.928571   \n",
+       "19                 20  {'n_neighbors': 20}           0.857143   \n",
+       "20                 21  {'n_neighbors': 21}           0.928571   \n",
+       "21                 22  {'n_neighbors': 22}           0.928571   \n",
+       "22                 23  {'n_neighbors': 23}           0.928571   \n",
+       "23                 24  {'n_neighbors': 24}           0.928571   \n",
+       "24                 25  {'n_neighbors': 25}           0.928571   \n",
+       "25                 26  {'n_neighbors': 26}           0.928571   \n",
+       "26                 27  {'n_neighbors': 27}           0.928571   \n",
+       "27                 28  {'n_neighbors': 28}           0.928571   \n",
+       "28                 29  {'n_neighbors': 29}           0.928571   \n",
+       "29                 30  {'n_neighbors': 30}           0.857143   \n",
+       "30                 31  {'n_neighbors': 31}           0.857143   \n",
+       "31                 32  {'n_neighbors': 32}           0.857143   \n",
+       "32                 33  {'n_neighbors': 33}           0.857143   \n",
+       "33                 34  {'n_neighbors': 34}           0.857143   \n",
+       "34                 35  {'n_neighbors': 35}           0.857143   \n",
+       "35                 36  {'n_neighbors': 36}           0.928571   \n",
+       "36                 37  {'n_neighbors': 37}           0.928571   \n",
+       "37                 38  {'n_neighbors': 38}           0.928571   \n",
+       "38                 39  {'n_neighbors': 39}           0.928571   \n",
+       "39                 40  {'n_neighbors': 40}           0.928571   \n",
+       "40                 41  {'n_neighbors': 41}           0.928571   \n",
+       "41                 42  {'n_neighbors': 42}           0.928571   \n",
+       "42                 43  {'n_neighbors': 43}           0.928571   \n",
+       "43                 44  {'n_neighbors': 44}           0.928571   \n",
+       "44                 45  {'n_neighbors': 45}           0.928571   \n",
+       "45                 46  {'n_neighbors': 46}           0.928571   \n",
+       "46                 47  {'n_neighbors': 47}           0.857143   \n",
+       "47                 48  {'n_neighbors': 48}           0.928571   \n",
+       "48                 49  {'n_neighbors': 49}           0.928571   \n",
+       "49                 50  {'n_neighbors': 50}           0.928571   \n",
+       "\n",
+       "    split1_test_score  split2_test_score  split3_test_score  \\\n",
+       "0            0.928571                1.0           0.692308   \n",
+       "1            0.928571                1.0           0.692308   \n",
+       "2            0.928571                1.0           0.846154   \n",
+       "3            0.928571                1.0           0.846154   \n",
+       "4            0.928571                1.0           0.923077   \n",
+       "5            1.000000                1.0           0.923077   \n",
+       "6            0.928571                1.0           0.923077   \n",
+       "7            1.000000                1.0           0.846154   \n",
+       "8            0.928571                1.0           0.923077   \n",
+       "9            0.928571                1.0           0.846154   \n",
+       "10           0.928571                1.0           0.923077   \n",
+       "11           0.928571                1.0           0.923077   \n",
+       "12           0.928571                1.0           1.000000   \n",
+       "13           0.928571                1.0           0.923077   \n",
+       "14           0.928571                1.0           0.923077   \n",
+       "15           0.928571                1.0           0.923077   \n",
+       "16           0.928571                1.0           0.923077   \n",
+       "17           0.928571                1.0           0.923077   \n",
+       "18           0.928571                1.0           0.923077   \n",
+       "19           0.928571                1.0           0.923077   \n",
+       "20           0.928571                1.0           0.923077   \n",
+       "21           0.928571                1.0           0.923077   \n",
+       "22           0.928571                1.0           0.923077   \n",
+       "23           0.928571                1.0           0.923077   \n",
+       "24           0.928571                1.0           0.846154   \n",
+       "25           0.928571                1.0           0.846154   \n",
+       "26           0.928571                1.0           0.846154   \n",
+       "27           0.928571                1.0           0.923077   \n",
+       "28           0.928571                1.0           0.923077   \n",
+       "29           0.928571                1.0           0.923077   \n",
+       "30           0.928571                1.0           0.923077   \n",
+       "31           0.928571                1.0           0.923077   \n",
+       "32           0.928571                1.0           0.923077   \n",
+       "33           0.928571                1.0           0.923077   \n",
+       "34           0.928571                1.0           0.923077   \n",
+       "35           0.928571                1.0           0.923077   \n",
+       "36           0.928571                1.0           0.923077   \n",
+       "37           0.928571                1.0           0.923077   \n",
+       "38           0.928571                1.0           0.923077   \n",
+       "39           0.928571                1.0           0.923077   \n",
+       "40           0.928571                1.0           1.000000   \n",
+       "41           0.928571                1.0           0.923077   \n",
+       "42           0.928571                1.0           0.923077   \n",
+       "43           0.928571                1.0           0.846154   \n",
+       "44           0.928571                1.0           0.846154   \n",
+       "45           0.928571                1.0           0.846154   \n",
+       "46           0.928571                1.0           0.923077   \n",
+       "47           0.928571                1.0           0.923077   \n",
+       "48           0.928571                1.0           0.923077   \n",
+       "49           0.928571                1.0           0.923077   \n",
+       "\n",
+       "    split4_test_score  split5_test_score  split6_test_score  \\\n",
+       "0            1.000000                1.0           1.000000   \n",
+       "1            1.000000                1.0           1.000000   \n",
+       "2            1.000000                1.0           1.000000   \n",
+       "3            0.923077                1.0           1.000000   \n",
+       "4            0.923077                1.0           1.000000   \n",
+       "5            0.923077                1.0           1.000000   \n",
+       "6            0.923077                1.0           1.000000   \n",
+       "7            0.923077                1.0           1.000000   \n",
+       "8            0.923077                1.0           1.000000   \n",
+       "9            0.923077                1.0           0.923077   \n",
+       "10           0.923077                1.0           1.000000   \n",
+       "11           0.923077                1.0           1.000000   \n",
+       "12           0.923077                1.0           1.000000   \n",
+       "13           0.923077                1.0           1.000000   \n",
+       "14           0.923077                1.0           1.000000   \n",
+       "15           0.923077                1.0           1.000000   \n",
+       "16           0.923077                1.0           1.000000   \n",
+       "17           0.923077                1.0           1.000000   \n",
+       "18           0.923077                1.0           1.000000   \n",
+       "19           0.923077                1.0           1.000000   \n",
+       "20           0.923077                1.0           1.000000   \n",
+       "21           0.923077                1.0           1.000000   \n",
+       "22           0.923077                1.0           1.000000   \n",
+       "23           0.923077                1.0           1.000000   \n",
+       "24           0.923077                1.0           1.000000   \n",
+       "25           0.923077                1.0           1.000000   \n",
+       "26           0.923077                1.0           1.000000   \n",
+       "27           0.923077                1.0           1.000000   \n",
+       "28           0.923077                1.0           1.000000   \n",
+       "29           0.923077                1.0           1.000000   \n",
+       "30           0.923077                1.0           1.000000   \n",
+       "31           0.923077                1.0           1.000000   \n",
+       "32           0.923077                1.0           1.000000   \n",
+       "33           0.923077                1.0           1.000000   \n",
+       "34           0.923077                1.0           0.923077   \n",
+       "35           0.923077                1.0           1.000000   \n",
+       "36           0.923077                1.0           1.000000   \n",
+       "37           0.923077                1.0           1.000000   \n",
+       "38           0.923077                1.0           1.000000   \n",
+       "39           0.923077                1.0           1.000000   \n",
+       "40           0.923077                1.0           1.000000   \n",
+       "41           0.923077                1.0           1.000000   \n",
+       "42           0.923077                1.0           1.000000   \n",
+       "43           0.923077                1.0           1.000000   \n",
+       "44           0.923077                1.0           1.000000   \n",
+       "45           0.923077                1.0           1.000000   \n",
+       "46           0.923077                1.0           1.000000   \n",
+       "47           0.923077                1.0           1.000000   \n",
+       "48           0.923077                1.0           1.000000   \n",
+       "49           0.923077                1.0           1.000000   \n",
+       "\n",
+       "    split7_test_score  split8_test_score  split9_test_score  mean_test_score  \\\n",
+       "0            1.000000           1.000000           0.923077         0.954396   \n",
+       "1            0.923077           0.923077           0.923077         0.939011   \n",
+       "2            1.000000           0.923077           0.923077         0.962088   \n",
+       "3            1.000000           0.923077           1.000000         0.954945   \n",
+       "4            1.000000           0.923077           1.000000         0.969780   \n",
+       "5            1.000000           0.923077           1.000000         0.969780   \n",
+       "6            1.000000           1.000000           1.000000         0.977473   \n",
+       "7            0.923077           0.923077           1.000000         0.954396   \n",
+       "8            0.923077           1.000000           1.000000         0.969780   \n",
+       "9            0.923077           1.000000           1.000000         0.954396   \n",
+       "10           0.923077           1.000000           1.000000         0.962637   \n",
+       "11           0.923077           1.000000           1.000000         0.969780   \n",
+       "12           0.923077           1.000000           1.000000         0.977473   \n",
+       "13           0.923077           1.000000           1.000000         0.962637   \n",
+       "14           0.923077           1.000000           1.000000         0.962637   \n",
+       "15           0.923077           1.000000           1.000000         0.962637   \n",
+       "16           0.923077           1.000000           1.000000         0.962637   \n",
+       "17           0.923077           1.000000           1.000000         0.962637   \n",
+       "18           0.923077           1.000000           1.000000         0.962637   \n",
+       "19           1.000000           1.000000           1.000000         0.963187   \n",
+       "20           1.000000           1.000000           1.000000         0.970330   \n",
+       "21           1.000000           1.000000           1.000000         0.970330   \n",
+       "22           1.000000           1.000000           0.923077         0.962637   \n",
+       "23           1.000000           1.000000           1.000000         0.970330   \n",
+       "24           1.000000           1.000000           0.923077         0.954945   \n",
+       "25           1.000000           1.000000           1.000000         0.962637   \n",
+       "26           1.000000           1.000000           0.923077         0.954945   \n",
+       "27           1.000000           1.000000           0.923077         0.962637   \n",
+       "28           1.000000           1.000000           0.923077         0.962637   \n",
+       "29           0.923077           1.000000           0.923077         0.947802   \n",
+       "30           1.000000           1.000000           0.923077         0.955495   \n",
+       "31           1.000000           1.000000           0.923077         0.955495   \n",
+       "32           1.000000           1.000000           0.923077         0.955495   \n",
+       "33           1.000000           1.000000           1.000000         0.963187   \n",
+       "34           1.000000           1.000000           1.000000         0.955495   \n",
+       "35           0.923077           1.000000           1.000000         0.962637   \n",
+       "36           0.923077           1.000000           1.000000         0.962637   \n",
+       "37           0.923077           1.000000           1.000000         0.962637   \n",
+       "38           0.923077           1.000000           1.000000         0.962637   \n",
+       "39           0.923077           1.000000           0.923077         0.954945   \n",
+       "40           0.923077           1.000000           1.000000         0.970330   \n",
+       "41           0.923077           1.000000           0.923077         0.954945   \n",
+       "42           0.923077           1.000000           0.923077         0.954945   \n",
+       "43           0.923077           1.000000           0.923077         0.947253   \n",
+       "44           0.923077           1.000000           0.923077         0.947253   \n",
+       "45           0.923077           1.000000           0.923077         0.947253   \n",
+       "46           0.923077           1.000000           0.923077         0.947802   \n",
+       "47           0.923077           0.923077           0.923077         0.947253   \n",
+       "48           0.923077           0.923077           0.923077         0.947253   \n",
+       "49           0.923077           0.923077           0.923077         0.947253   \n",
+       "\n",
+       "    std_test_score  rank_test_score  \n",
+       "0         0.092139               39  \n",
+       "1         0.089628               50  \n",
+       "2         0.051217               28  \n",
+       "3         0.050406               35  \n",
+       "4         0.037042                7  \n",
+       "5         0.037042                7  \n",
+       "6         0.034441                1  \n",
+       "7         0.050719               39  \n",
+       "8         0.037042                9  \n",
+       "9         0.050719               39  \n",
+       "10        0.037411               17  \n",
+       "11        0.037042                9  \n",
+       "12        0.034441                1  \n",
+       "13        0.037411               17  \n",
+       "14        0.037411               17  \n",
+       "15        0.037411               17  \n",
+       "16        0.037411               17  \n",
+       "17        0.037411               17  \n",
+       "18        0.037411               17  \n",
+       "19        0.048777               11  \n",
+       "20        0.036380                3  \n",
+       "21        0.036380                3  \n",
+       "22        0.037411               13  \n",
+       "23        0.036380                3  \n",
+       "24        0.050406               33  \n",
+       "25        0.050823               13  \n",
+       "26        0.050406               33  \n",
+       "27        0.037411               13  \n",
+       "28        0.037411               13  \n",
+       "29        0.046832               42  \n",
+       "30        0.048430               29  \n",
+       "31        0.048430               29  \n",
+       "32        0.048430               29  \n",
+       "33        0.048777               11  \n",
+       "34        0.048430               29  \n",
+       "35        0.037411               17  \n",
+       "36        0.037411               17  \n",
+       "37        0.037411               17  \n",
+       "38        0.037411               17  \n",
+       "39        0.036842               35  \n",
+       "40        0.036380                3  \n",
+       "41        0.036842               35  \n",
+       "42        0.036842               35  \n",
+       "43        0.048787               44  \n",
+       "44        0.048787               44  \n",
+       "45        0.048787               44  \n",
+       "46        0.046832               42  \n",
+       "47        0.034594               44  \n",
+       "48        0.034594               44  \n",
+       "49        0.034594               44  "
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here..."
+    "knn = KNeighborsClassifier()\n",
+    "\n",
+    "parameter_grid = {\n",
+    "    \"n_neighbors\": range(1,51)\n",
+    "}\n",
+    "\n",
+    "wine_tune_grid = GridSearchCV(\n",
+    "    estimator=knn,\n",
+    "    param_grid=parameter_grid,\n",
+    "    cv=10\n",
+    ")\n",
+    "\n",
+    "X_train = wine_train.iloc[:, :-1]   # all columns except last\n",
+    "y_train = wine_train['class'] \n",
+    "\n",
+    "wine_tune_grid.fit(X_train, y_train)\n",
+    "\n",
+    "accuracy_grid = pd.DataFrame(wine_tune_grid.cv_results_)\n",
+    "accuracy_grid\n"
    ]
   },
   {
@@ -305,12 +2401,47 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "id": "ffefa9f2",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9411764705882353"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here..."
+    "kvalue = wine_tune_grid.best_params_[\"n_neighbors\"]\n",
+    "\n",
+    "wine_subtrain, wine_validation = train_test_split(\n",
+    "    wine_train,\n",
+    "    train_size=0.75,\n",
+    "    stratify=wine_train['class']\n",
+    ")\n",
+    "\n",
+    "X_sub = wine_subtrain.iloc[:, :-1]\n",
+    "y_sub = wine_subtrain['class']\n",
+    "\n",
+    "X_val = wine_validation.iloc[:, :-1]\n",
+    "y_val = wine_validation['class']\n",
+    "\n",
+    "# 3. Fit final KNN using best k\n",
+    "final_knn = KNeighborsClassifier(n_neighbors=kvalue)\n",
+    "final_knn.fit(X_sub, y_sub)\n",
+    "\n",
+    "# 4. Predict on validation set\n",
+    "val_predictions = final_knn.predict(X_val)\n",
+    "\n",
+    "# 5. Accuracy on validation set\n",
+    "val_accuracy = accuracy_score(y_val, val_predictions)\n",
+    "val_accuracy\n",
+    "\n"
    ]
   },
   {
@@ -365,7 +2496,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.4",
+   "display_name": "lcr-env",
    "language": "python",
    "name": "python3"
   },
@@ -379,12 +2510,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "497a84dc8fec8cf8d24e7e87b6d954c9a18a327edc66feb9b9ea7e9e72cc5c7e"
-   }
+   "version": "3.11.1"
   }
  },
  "nbformat": 4,
diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb
index a05da5cd3..6d35e44f5 100644
--- a/02_activities/assignments/assignment_2.ipynb
+++ b/02_activities/assignments/assignment_2.ipynb
@@ -34,10 +34,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": null,
    "id": "4a3485d6-ba58-4660-a983-5680821c5719",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31mFailed to start the Kernel. \n",
+      "\u001b[1;31mUnable to start Kernel 'lcr-env (Python 3.11.1)' due to a timeout waiting for the ports to get used. \n",
+      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
+     ]
+    }
+   ],
    "source": [
     "# Import standard libraries\n",
     "import pandas as pd\n",
@@ -87,7 +98,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your answer here..."
+    "mpg_data.shape\n",
+    "#rows,columns"
    ]
   },
   {
@@ -105,7 +117,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your answer here..."
+    "mpg_data['mpg'].info()"
    ]
   },
   {
@@ -113,7 +125,7 @@
    "id": "6d759089",
    "metadata": {},
    "source": [
-    "Your explanation... \n"
+    "A float is a data type used to represent numbers that have a decimal point.\n"
    ]
   },
   {
@@ -131,7 +143,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your answer here... "
+    "mpg_data['horsepower'].nlargest(5)"
    ]
   },
   {
@@ -149,7 +161,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your answer here..."
+    "len(mpg_data.columns) - 1"
    ]
   },
   {
@@ -225,7 +237,12 @@
    "id": "f67e57ab",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "Positive association between miles per gallon and acceleration.\n",
+    "Negative assoication between miles per gallon and cylinders. \n",
+    "Negative assoication between miles per gallon and displacement. \n",
+    "Negative assoication between miles per gallon and horsepower. \n",
+    "Positive association between miles per gallon and model year.\n",
+    "Negative assoication between miles per gallon and weight. "
    ]
   },
   {
@@ -241,7 +258,7 @@
    "id": "843f9eef",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "This line is mathematically determined to represent the best possible linear summary of the relationship between the independent (predictor) variable and the dependent (response) variable in a dataset. "
    ]
   },
   {
@@ -257,7 +274,7 @@
    "id": "2ea782fc",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "Data points do not always or usually fall perfectly on the regression line, this is because the line only reflects the averaged relationship between two factors. Each point is influenced by many factors, causing deviations and noise. "
    ]
   },
   {
@@ -279,7 +296,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your answer here..."
+    "mpg_train, mpg_test = train_test_split(\n",
+    "    mpg_data, train_size=0.75, random_state=42\n",
+    ")"
    ]
   },
   {
@@ -299,12 +318,18 @@
    "source": [
     "# Your code here ...\n",
     "\n",
-    "numeric_predictors = 🤷‍♂️\n",
+    "numeric_predictors = ['cylinders', 'displacement', 'horsepower', 'weight', 'acceleration']\n",
+    "\n",
+    "lm = LinearRegression()\n",
+    "lm.fit(\n",
+    "   mpg_train[numeric_predictors],  # A single-column data frame (square footage)\n",
+    "   mpg_train[\"mpg\"]  # A series (house prices)\n",
+    ")\n",
     "\n",
     "\n",
     "# Create a DataFrame containing the slope (coefficients) and intercept\n",
     "coefficients_df = pd.DataFrame({\n",
-    "    \"predictor\": numeric_predictors.columns,\n",
+    "    \"predictor\": numeric_predictors,\n",
     "    \"slope\": lm.coef_,\n",
     "    \"intercept\": [lm.intercept_] * len(lm.coef_)\n",
     "})\n",
@@ -335,7 +360,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here ..."
+    "mpg_test[\"predicted\"] = lm.predict(mpg_test[numeric_predictors])\n",
+    "\n",
+    "# Calculate RMSPE\n",
+    "lm_rmspe = mean_squared_error(\n",
+    "    y_true=mpg_test[\"mpg\"], # actual sale prices\n",
+    "    y_pred=mpg_test[\"predicted\"] # the value predicted by the model\n",
+    ")**1/2\n",
+    "\n",
+    "lm_rmspe"
    ]
   },
   {
@@ -386,7 +419,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "lcr-env",
    "language": "python",
    "name": "python3"
   },
@@ -400,12 +433,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "497a84dc8fec8cf8d24e7e87b6d954c9a18a327edc66feb9b9ea7e9e72cc5c7e"
-   }
+   "version": "3.11.1"
   }
  },
  "nbformat": 4,
diff --git a/02_activities/assignments/assignment_3.ipynb b/02_activities/assignments/assignment_3.ipynb
index 889b10f21..f0c048d0b 100644
--- a/02_activities/assignments/assignment_3.ipynb
+++ b/02_activities/assignments/assignment_3.ipynb
@@ -76,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "a431d282-f9ca-4d5d-8912-71ffc9d8ea19",
    "metadata": {},
    "outputs": [
@@ -138,7 +138,9 @@
     "# Display the DataFrame\n",
     "print(wine_df)\n",
     "\n",
-    "# Your code here..."
+    "#code here\n",
+    "row, col = wine_df.shape\n",
+    "print('rows:', row, \",\", \"columns:\", col)"
    ]
   },
   {
@@ -232,7 +234,7 @@
    "id": "35308e2c",
    "metadata": {},
    "source": [
-    "> Your answer..."
+    "Malic acids and flavanoids seems to distinctively form separate clusters. "
    ]
   },
   {
@@ -301,10 +303,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "53d77d5c",
+   "id": "69f7bb7f",
    "metadata": {},
    "source": [
-    "> Your answer here ... "
+    "Depending on the range of values, when you compare larger ranges to smaller ranges, the differences in changes will be weighted differently when assessing their impact on the clusters. By using standardized data, it assesses the relatively range of the values for each values opposed to the absolute values. "
    ]
   },
   {
@@ -325,13 +327,20 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your answer...\n",
     "\n",
-    "clustered_wine_data = 🤷‍♂️\n",
+    "clustered_wine_data = KMeans(n_clusters=3, random_state=12)\n",
+    "\n",
+    "# fit cluster to our data \n",
+    "clusters = clustered_wine_data.fit(scaled_wine_df)\n",
+    "\n",
+    "scaled_wine_clusters = scaled_wine_df.copy()\n",
+    "\n",
+    "\n",
+    "scaled_wine_clusters['Cluster'] = clusters.labels_\n",
     "\n",
     "\n",
     "# Use the helper function to plot scatter plots, colored by cluster labels\n",
-    "plot_feature_pairs(clustered_wine_data, feature_names, color_labels=clustered_wine_data['Cluster'], title_prefix='Clustered Data: ')"
+    "plot_feature_pairs(scaled_wine_clusters, feature_names, color_labels=scaled_wine_clusters['Cluster'], title_prefix='Clustered Data: ')"
    ]
   },
   {
@@ -349,7 +358,7 @@
    "id": "83349688",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "Answer: Running a forloop using a range of K values to determine where the elbow point is - i.e. where increasing the number of clusters no longer leads to meaningful reduction in WSSD."
    ]
   },
   {
@@ -371,13 +380,28 @@
    "outputs": [],
    "source": [
     "# Your answer here...\n",
+    "bootstrap_samples = []\n",
     "\n",
-    "mean_color_intensity = 🤷‍♂️\n",
+    "for i in range(10_000):\n",
+    "    sample = wine_df.sample(n=len(wine_df), replace=True)  # Sample with replacement\n",
+    "    sample = sample.assign(replicate=i)  # Add replicate number\n",
+    "    bootstrap_samples.append(sample)  # Store the sample\n",
+    "\n",
+    "# Combine all bootstrap samples into one DataFrame\n",
+    "boot20000 = pd.concat(bootstrap_samples)\n",
+    "\n",
+    "\n",
+    "\n",
+    "# generating the table with the means of each bootstrap\n",
+    "summary_mean_color_intensity = boot20000.groupby('replicate')['color_intensity'].mean().reset_index(name='mean_color_intesity')\n",
+    "#generating the final mean\n",
+    "mean_color_intensity = summary_mean_color_intensity[\"mean_color_intesity\"].mean()\n",
     "\n",
     "np.random.seed(123)\n",
     "\n",
-    "lower_bound = 🤷‍♂️\n",
-    "upper_bound = 🤷‍♂️\n",
+    "lower_bound = summary_mean_color_intensity[\"mean_color_intesity\"].quantile(0.05)\n",
+    "upper_bound = summary_mean_color_intensity[\"mean_color_intesity\"].quantile(0.95)\n",
+    "\n",
     "\n",
     "# Display the result\n",
     "print(f\"Mean of Color Intensity: {mean_color_intensity}\")\n",
@@ -398,7 +422,7 @@
    "id": "16a6e104",
    "metadata": {},
    "source": [
-    ">  Your answer..."
+    "In this case, we can sample a small sub-set of the total number of wines, and make an estimate about the colour intensity of all the wines in a collection "
    ]
   },
   {
@@ -415,7 +439,7 @@
    "id": "e5be82ec",
    "metadata": {},
    "source": [
-    "> Your answer..."
+    "It tells us that our estimate is 90% likely to be true. A smaller range indicates a higher confidence in the mean value, whereas a wider range indicates a smaller confidence in the true mean value. "
    ]
   },
   {
@@ -433,7 +457,7 @@
    "id": "0a7e6778",
    "metadata": {},
    "source": [
-    "> Your answer here..."
+    "Our confidence intervals are very narrow, and close to the estimated mean, suggesting that our bootstrapping and the color intensity values tend to be very stable. "
    ]
   },
   {