update

Author: mhjensen

doc/pub/week47/html/._week47-bs001.html

@@ -367,7 +367,6 @@ <h2 id="plan-for-week-47" class="anchor">Plan for week 47 </h2>
  <li> Video on Gradient boost, part 1, parts 2-4 follow thereafter <a href="https://www.youtube.com/watch?v=3CC4N4z3GJc" target="_self"><tt>https://www.youtube.com/watch?v=3CC4N4z3GJc</tt></a></li>
  <li> Decision Trees: Rashcka et al chapter 3 pages 86-98, and chapter 7 on Ensemble methods, Voting and Bagging and Gradient Boosting. See also lecture from STK-IN4300, lecture 7 at <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf" target="_self"><tt>https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf</tt></a>.</li> 
 </ol>
-<li> Decision Trees: Geron's chapter 6 covers decision trees while ensemble models, voting and bagging are discussed in chapter 7. See also lecture from <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf" target="_self">STK-IN4300, lecture 7</a>. Chapter 9.2 of Hastie et al contains also a good discussion.</li>
 </ol>
 </div>
 </div>

doc/pub/week47/html/week47-reveal.html

@@ -227,7 +227,6 @@ <h2 id="plan-for-week-47">Plan for week 47 </h2>
  <p><li> Decision Trees: Rashcka et al chapter 3 pages 86-98, and chapter 7 on Ensemble methods, Voting and Bagging and Gradient Boosting. See also lecture from STK-IN4300, lecture 7 at <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf" target="_blank"><tt>https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf</tt></a>.</li> 
 </ol>
 <p>
-<p><li> Decision Trees: Geron's chapter 6 covers decision trees while ensemble models, voting and bagging are discussed in chapter 7. See also lecture from <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf" target="_blank">STK-IN4300, lecture 7</a>. Chapter 9.2 of Hastie et al contains also a good discussion.</li>
 </ol>
 </div>
 </section>

doc/pub/week47/html/week47-solarized.html

@@ -325,7 +325,6 @@ <h2 id="plan-for-week-47">Plan for week 47 </h2>
  <li> Video on Gradient boost, part 1, parts 2-4 follow thereafter <a href="https://www.youtube.com/watch?v=3CC4N4z3GJc" target="_blank"><tt>https://www.youtube.com/watch?v=3CC4N4z3GJc</tt></a></li>
  <li> Decision Trees: Rashcka et al chapter 3 pages 86-98, and chapter 7 on Ensemble methods, Voting and Bagging and Gradient Boosting. See also lecture from STK-IN4300, lecture 7 at <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf" target="_blank"><tt>https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf</tt></a>.</li> 
 </ol>
-<li> Decision Trees: Geron's chapter 6 covers decision trees while ensemble models, voting and bagging are discussed in chapter 7. See also lecture from <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf" target="_blank">STK-IN4300, lecture 7</a>. Chapter 9.2 of Hastie et al contains also a good discussion.</li>
 </ol>
 </div>
 

doc/pub/week47/html/week47.html

@@ -402,7 +402,6 @@ <h2 id="plan-for-week-47">Plan for week 47 </h2>
  <li> Video on Gradient boost, part 1, parts 2-4 follow thereafter <a href="https://www.youtube.com/watch?v=3CC4N4z3GJc" target="_blank"><tt>https://www.youtube.com/watch?v=3CC4N4z3GJc</tt></a></li>
  <li> Decision Trees: Rashcka et al chapter 3 pages 86-98, and chapter 7 on Ensemble methods, Voting and Bagging and Gradient Boosting. See also lecture from STK-IN4300, lecture 7 at <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf" target="_blank"><tt>https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf</tt></a>.</li> 
 </ol>
-<li> Decision Trees: Geron's chapter 6 covers decision trees while ensemble models, voting and bagging are discussed in chapter 7. See also lecture from <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf" target="_blank">STK-IN4300, lecture 7</a>. Chapter 9.2 of Hastie et al contains also a good discussion.</li>
 </ol>
 </div>
 

doc/pub/week47/ipynb/DataFiles/cancer.dot

@@ -1,57 +1,57 @@
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 1 -> 11 ;
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 0 -> 14 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
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+15 [label="worst concavity <= 0.318\ngini = 0.375\nsamples = 16\nvalue = [[12, 4]\n[4, 12]]", fillcolor="#f9e3d4"] ;
 14 -> 15 ;
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 15 -> 17 ;
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 17 -> 18 ;
-19 [label="gini = 0.0\nsamples = 4\nvalue = [[0, 4]\n[4, 0]]", fillcolor="#e58139ff"] ;
+19 [label="gini = 0.0\nsamples = 4\nvalue = [[0, 4]\n[4, 0]]", fillcolor="#e58139"] ;
 17 -> 19 ;
-20 [label="mean concave points <= 0.049\ngini = 0.088\nsamples = 151\nvalue = [[7, 144]\n[144, 7]]", fillcolor="#e58139d0"] ;
+20 [label="mean concave points <= 0.049\ngini = 0.088\nsamples = 151\nvalue = [[7, 144]\n[144, 7]]", fillcolor="#ea985d"] ;
 14 -> 20 ;
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 20 -> 21 ;
-22 [label="gini = 0.0\nsamples = 9\nvalue = [[0, 9]\n[9, 0]]", fillcolor="#e58139ff"] ;
+22 [label="gini = 0.0\nsamples = 9\nvalue = [[0, 9]\n[9, 0]]", fillcolor="#e58139"] ;
 21 -> 22 ;
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+23 [label="gini = 0.0\nsamples = 6\nvalue = [[6, 0]\n[0, 6]]", fillcolor="#e58139"] ;
 21 -> 23 ;
-24 [label="worst smoothness <= 0.096\ngini = 0.015\nsamples = 136\nvalue = [[1, 135]\n[135, 1]]", fillcolor="#e58139f7"] ;
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 24 -> 26 ;
 }

doc/pub/week47/ipynb/DataFiles/cancer.png

@@ -1,13 +1,13 @@
 digraph Tree {
-node [shape=box, style="filled, rounded", color="black", fontname=helvetica] ;
-edge [fontname=helvetica] ;
-0 [label="X[7] <= 0.5\ngini = 0.48\nsamples = 15\nvalue = [4, 10, 1]", fillcolor="#39e5818b"] ;
-1 [label="X[1] <= 0.5\ngini = 0.408\nsamples = 14\nvalue = [4, 10, 0]", fillcolor="#39e58199"] ;
+node [shape=box, style="filled, rounded", color="black", fontname="helvetica"] ;
+edge [fontname="helvetica"] ;
+0 [label="x[13] <= 0.5\ngini = 0.48\nsamples = 15\nvalue = [4, 10, 1]", fillcolor="#93f1ba"] ;
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 0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
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 1 -> 2 ;
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