ElasticNetRegression.rtf

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{\fdbminor\f31558\fbidi \froman\fcharset238\fprq2 Times New Roman CE;}{\fdbminor\f31559\fbidi \froman\fcharset204\fprq2 Times New Roman Cyr;}{\fdbminor\f31561\fbidi \froman\fcharset161\fprq2 Times New Roman Greek;}
{\fdbminor\f31562\fbidi \froman\fcharset162\fprq2 Times New Roman Tur;}{\fdbminor\f31563\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}{\fdbminor\f31564\fbidi \froman\fcharset178\fprq2 Times New Roman (Arabic);}
{\fdbminor\f31565\fbidi \froman\fcharset186\fprq2 Times New Roman Baltic;}{\fdbminor\f31566\fbidi \froman\fcharset163\fprq2 Times New Roman (Vietnamese);}{\fhiminor\f31568\fbidi \fswiss\fcharset238\fprq2 Calibri CE;}
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{\pntxtb (}{\pntxta )}}{\*\pnseclvl9\pnlcrm\pnstart1\pnindent720\pnhang {\pntxtb (}{\pntxta )}}\pard\plain \ltrpar\ql \li0\ri0\sa160\sl259\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid3218741 \rtlch\fcs1 
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\par     "session_name": "test",
\par     "session_description": "test",
\par     "design_state_data": \{
\par 
\par       "session_info" : \{
\par         "project_id": "1",
\par         "experiment_id": "kkkk-11",
\par         "dataset":"iris_modified.csv",
\par         "session_name": "test",
\par         "session_description": "test"
\par         \},
\par 
\par       "target": \{
\par         "prediction_type": "Classification",
\par         "target": "species",
\par         "type":"classifiation",
\par         "partitioning": true
\par       \},
\par       "train": \{
\par         "policy": "Split the dataset",
\par         "time_variable": "sepal_length",
\par         "sampling_method": "No sampling(whole data)",
\par         "split": "Randomly",
\par         "k_fold": false,
\par         "train_ratio": 0.8,
\par         "random_seed": }{\rtlch\fcs1 \af2\afs21 \ltrch\fcs0 \f2\fs21\insrsid12154272 1}{\rtlch\fcs1 \af2\afs21 \ltrch\fcs0 \f2\fs21\insrsid3218741\charrsid3218741 0
\par       \},
\par       "feature_handling": \{
\par         "sepal_length": \{
\par           "feature_name": "sepal_length",
\par           "is_selected": true,
\par           "feature_variable_type": "numerical",
\par           "feature_details": \{
\par             "numerical_handling": "Keep as regular numerical feature",
\par             "rescaling": "No rescaling",
\par             "make_derived_feats": false,
\par             "missing_values": "Impute",
\par             "impute_with": "Average of values"
\par             
\par           \}
\par         \},
\par         "sepal_width": \{
\par           "feature_name": "sepal_width",
\par           "is_selected": true,
\par           "feature_variable_type": "numerical",
\par           "feature_details": \{
\par             "numerical_handling": "Keep as regular numerical feature",
\par             "rescaling": "No rescaling",
\par             "make_derived_feats": false,
\par             "missing_values": "Impute",
\par             "impute_with": "Average of values"
\par             
\par           \}
\par         \},
\par         "petal_length": \{
\par           "feature_name": "petal_length",
\par           "is_selected": true,
\par           "feature_variable_type": "numerical",
\par           "feature_details": \{
\par             "numerical_handling": "Keep as regular numerical feature",
\par             "rescaling": "No rescaling",
\par             "make_derived_feats": false,
\par             "missing_values": "Impute",
\par             "impute_with": "Average of values"
\par             
\par           \}
\par         \},
\par         "petal_width": \{
\par           "feature_name": "petal_width",
\par           "is_selected": }{\rtlch\fcs1 \af2\afs21 \ltrch\fcs0 \f2\fs21\insrsid1526327 false}{\rtlch\fcs1 \af2\afs21 \ltrch\fcs0 \f2\fs21\insrsid3218741\charrsid3218741 ,
\par           "feature_variable_type": "numerical",
\par           "feature_details": \{
\par             "numerical_handling": "Keep as regular numerical feature",
\par             "rescaling": "No rescaling",
\par             "make_derived_feats": false,
\par             "missing_values": "Impute",
\par             "impute_with": "Average of values"            
\par           \}
\par         \},
\par         "species": \{
\par           "feature_name": "species",
\par           "is_selected": true,
\par           "feature_variable_type": "text",
\par           "feature_details": \{
\par             "text_handling": "Tokenize and hash",
\par             "hash_columns": 0
\par           \}
\par         \}
\par       \},
\par       
\par       "algorithms": \{
\par         "RandomForestClassifier": \{
\par           "model_name": "Random Forest Classifier",
\par           "is_selected": false,
\par           "min_trees": 10,
\par           "max_trees": 30,
\par           "feature_sampling_statergy": "Default",
\par           "min_depth": 20,
\par           "max_depth": 30,
\par           "min_samples_per_leaf_min_value": 5,
\par           "min_samples_per_leaf_max_value": 50,
\par           "parallelism": 0
\par         \},
\par         "RandomForestRegressor": \{
\par           "model_name": "Random Forest Regressor",
\par           "is_selected": false,
\par           "min_trees": 10,
\par           "max_trees": 20,
\par           "feature_sampling_statergy": "Default",
\par           "min_depth": 20,
\par           "max_depth": 25,
\par           "min_samples_per_leaf_min_value": 5,
\par           "min_samples_per_leaf_max_value": 10,
\par           "parallelism": 0
\par         \},
\par }\pard \ltrpar\ql \li0\ri0\sa160\sl259\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid12544274 {\rtlch\fcs1 \af2\afs21 \ltrch\fcs0 \f2\fs21\insrsid3218741\charrsid3218741         
\par }\pard \ltrpar\ql \li0\ri0\sa160\sl259\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid3218741 {\rtlch\fcs1 \af2\afs21 \ltrch\fcs0 \f2\fs21\insrsid3218741\charrsid3218741         "LinearRegression": \{
\par           "model_name": "LinearRegression",
\par           "is_selected": false,
\par           "parallelism": 2,
\par           "min_iter":30,
\par           "max_iter":50,
\par           "min_regparam":0.5,
\par           "max_regparam":0.8,
\par           "min_elasticnet":0.5,
\par           "max_elasticnet":0.8
\par         \},
\par         "LogisticRegression": \{
\par           "model_name": "LogisticRegression",
\par           "is_selected": false,
\par           "parallelism": 2,
\par           "min_iter":30,
\par           "max_iter":50,
\par           "min_regparam":0.5,
\par           "max_regparam":0.8,
\par           "min_elasticnet":0.5,
\par           "max_elasticnet":0.8
\par         \},
\par         "RidgeRegression": \{
\par           "model_name": "RidgeRegression",
\par           "is_selected": false,
\par           "regularization_term": "Specify values to test",
\par           "min_iter":30,
\par           "max_iter":50,
\par           "min_regparam":0.5,
\par           "max_regparam":0.8
\par         \},
\par         "LassoRegression": \{
\par           "model_name": "Lasso Regression",
\par           "is_selected": false,
\par           "regularization_term": "Specify values to test",
\par           "min_iter":30,
\par           "max_iter":50,
\par           "min_regparam":0.5,
\par           "max_regparam":0.8
\par         \},
\par         "ElasticNetRegression": \{
\par           "model_name": "Lasso Regression",
\par           "is_selected": true,
\par           "regularization_term": "Specify values to test",
\par           "min_iter":30,
\par           "max_iter":50,
\par           "min_regparam":0.5,
\par           "max_regparam":0.8,
\par           "min_elasticnet":0.5,
\par           "max_elasticnet":0.8
\par         \},
\par         "xg_boost": \{
\par           "model_name": "XG Boost",
\par           "is_selected": false,
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