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DT_Classifier.rtf

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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,
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+\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": 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           "min_elasticnet":0.5,
+\par           "max_elasticnet":0.8
+\par         \},
+\par         "xg_boost": \{
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DT_Regressor.rtf

@@ -0,0 +1,465 @@
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+{\f34\fbidi \froman\fcharset0\fprq2{\*\panose 02040503050406030204}Cambria Math;}{\f37\fbidi \fswiss\fcharset0\fprq2{\*\panose 020f0502020204030204}Calibri;}{\f43\fbidi \fmodern\fcharset0\fprq1{\*\panose 020b0609020204030204}Consolas;}
+{\flomajor\f31500\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}{\fdbmajor\f31501\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}
+{\fhimajor\f31502\fbidi \fswiss\fcharset0\fprq2{\*\panose 020f0302020204030204}Calibri Light;}{\fbimajor\f31503\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}
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+{\fhiminor\f31506\fbidi \fswiss\fcharset0\fprq2{\*\panose 020f0502020204030204}Calibri;}{\fbiminor\f31507\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}{\f44\fbidi \froman\fcharset238\fprq2 Times New Roman CE;}
+{\f45\fbidi \froman\fcharset204\fprq2 Times New Roman Cyr;}{\f47\fbidi \froman\fcharset161\fprq2 Times New Roman Greek;}{\f48\fbidi \froman\fcharset162\fprq2 Times New Roman Tur;}{\f49\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}
+{\f50\fbidi \froman\fcharset178\fprq2 Times New Roman (Arabic);}{\f51\fbidi \froman\fcharset186\fprq2 Times New Roman Baltic;}{\f52\fbidi \froman\fcharset163\fprq2 Times New Roman (Vietnamese);}{\f64\fbidi \fmodern\fcharset238\fprq1 Courier New CE;}
+{\f65\fbidi \fmodern\fcharset204\fprq1 Courier New Cyr;}{\f67\fbidi \fmodern\fcharset161\fprq1 Courier New Greek;}{\f68\fbidi \fmodern\fcharset162\fprq1 Courier New Tur;}{\f69\fbidi \fmodern\fcharset177\fprq1 Courier New (Hebrew);}
+{\f70\fbidi \fmodern\fcharset178\fprq1 Courier New (Arabic);}{\f71\fbidi \fmodern\fcharset186\fprq1 Courier New Baltic;}{\f72\fbidi \fmodern\fcharset163\fprq1 Courier New (Vietnamese);}{\f384\fbidi \froman\fcharset238\fprq2 Cambria Math CE;}
+{\f385\fbidi \froman\fcharset204\fprq2 Cambria Math Cyr;}{\f387\fbidi \froman\fcharset161\fprq2 Cambria Math Greek;}{\f388\fbidi \froman\fcharset162\fprq2 Cambria Math Tur;}{\f391\fbidi \froman\fcharset186\fprq2 Cambria Math Baltic;}
+{\f392\fbidi \froman\fcharset163\fprq2 Cambria Math (Vietnamese);}{\f414\fbidi \fswiss\fcharset238\fprq2 Calibri CE;}{\f415\fbidi \fswiss\fcharset204\fprq2 Calibri Cyr;}{\f417\fbidi \fswiss\fcharset161\fprq2 Calibri Greek;}
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ElasticNetRegression.rtf

@@ -0,0 +1,465 @@
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+ml}}\paperw12240\paperh15840\margl1501\margr1502\margt1440\margb1440\gutter0\ltrsect 
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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 
+\af0\afs22\alang1025 \ltrch\fcs0 \f31506\fs22\lang1033\langfe1033\cgrid\langnp1033\langfenp1033 {\rtlch\fcs1 \af2\afs21 \ltrch\fcs0 \f2\fs21\insrsid3218741\charrsid3218741 \{
+\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": \{
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KNN.rtf

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LassoRegression.rtf

@@ -0,0 +1,465 @@
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+\par 
+\par       "session_info" : \{
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+\par         "experiment_id": "kkkk-11",
+\par         "dataset":"iris_modified.csv",
+\par         "session_name": "test",
+\par         "session_description": "test"
+\par         \},
+\par 
+\par       "target": \{
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+\par         "target": "species",
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+\par       \},
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+\par       \},
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+\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         \},
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+\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": \{
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+\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": \{
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+\par           "is_selected": false,
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+\par           "min_samples_per_leaf_max_value": 50,
+\par           "parallelism": 0
+\par         \},
+\par         "RandomForestRegressor": \{
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+\par           "is_selected": false,
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+\par           "feature_sampling_statergy": "Default",
+\par           "min_depth": 20,
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+\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": \{
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+\par           "min_iter":30,
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+\par         \},
+\par         "LassoRegression": \{
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+\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": \{
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+\par           "is_selected": false,
+\par           "regularization_term": "Specify values to test",
+\par           "min_iter":30,
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+\par           "max_elasticnet":0.8
+\par         \},
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+\par           "is_selected": false,
+\par           "use_gradient_boosted_tree": true,
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LogisticRegression.rtf

@@ -0,0 +1,465 @@
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Neural_Network.rtf

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+ml}}\paperw12240\paperh15840\margl1501\margr1502\margt1440\margb1440\gutter0\ltrsect 
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+\af0\afs22\alang1025 \ltrch\fcs0 \f31506\fs22\lang1033\langfe1033\cgrid\langnp1033\langfenp1033 {\rtlch\fcs1 \af2\afs21 \ltrch\fcs0 \f2\fs21\insrsid3218741\charrsid3218741 \{
+\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": \{
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RF_Classifier.rtf

@@ -0,0 +1,465 @@
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+{\f34\fbidi \froman\fcharset0\fprq2{\*\panose 02040503050406030204}Cambria Math;}{\f37\fbidi \fswiss\fcharset0\fprq2{\*\panose 020f0502020204030204}Calibri;}{\f43\fbidi \fmodern\fcharset0\fprq1{\*\panose 020b0609020204030204}Consolas;}
+{\flomajor\f31500\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}{\fdbmajor\f31501\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}
+{\fhimajor\f31502\fbidi \fswiss\fcharset0\fprq2{\*\panose 020f0302020204030204}Calibri Light;}{\fbimajor\f31503\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}
+{\flominor\f31504\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}{\fdbminor\f31505\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}
+{\fhiminor\f31506\fbidi \fswiss\fcharset0\fprq2{\*\panose 020f0502020204030204}Calibri;}{\fbiminor\f31507\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}{\f44\fbidi \froman\fcharset238\fprq2 Times New Roman CE;}
+{\f45\fbidi \froman\fcharset204\fprq2 Times New Roman Cyr;}{\f47\fbidi \froman\fcharset161\fprq2 Times New Roman Greek;}{\f48\fbidi \froman\fcharset162\fprq2 Times New Roman Tur;}{\f49\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}
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+{\f65\fbidi \fmodern\fcharset204\fprq1 Courier New Cyr;}{\f67\fbidi \fmodern\fcharset161\fprq1 Courier New Greek;}{\f68\fbidi \fmodern\fcharset162\fprq1 Courier New Tur;}{\f69\fbidi \fmodern\fcharset177\fprq1 Courier New (Hebrew);}
+{\f70\fbidi \fmodern\fcharset178\fprq1 Courier New (Arabic);}{\f71\fbidi \fmodern\fcharset186\fprq1 Courier New Baltic;}{\f72\fbidi \fmodern\fcharset163\fprq1 Courier New (Vietnamese);}{\f384\fbidi \froman\fcharset238\fprq2 Cambria Math CE;}
+{\f385\fbidi \froman\fcharset204\fprq2 Cambria Math Cyr;}{\f387\fbidi \froman\fcharset161\fprq2 Cambria Math Greek;}{\f388\fbidi \froman\fcharset162\fprq2 Cambria Math Tur;}{\f391\fbidi \froman\fcharset186\fprq2 Cambria Math Baltic;}
+{\f392\fbidi \froman\fcharset163\fprq2 Cambria Math (Vietnamese);}{\f414\fbidi \fswiss\fcharset238\fprq2 Calibri CE;}{\f415\fbidi \fswiss\fcharset204\fprq2 Calibri Cyr;}{\f417\fbidi \fswiss\fcharset161\fprq2 Calibri Greek;}
+{\f418\fbidi \fswiss\fcharset162\fprq2 Calibri Tur;}{\f419\fbidi \fswiss\fcharset177\fprq2 Calibri (Hebrew);}{\f420\fbidi \fswiss\fcharset178\fprq2 Calibri (Arabic);}{\f421\fbidi \fswiss\fcharset186\fprq2 Calibri Baltic;}
+{\f422\fbidi \fswiss\fcharset163\fprq2 Calibri (Vietnamese);}{\f474\fbidi \fmodern\fcharset238\fprq1 Consolas CE;}{\f475\fbidi \fmodern\fcharset204\fprq1 Consolas Cyr;}{\f477\fbidi \fmodern\fcharset161\fprq1 Consolas Greek;}
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+{\flomajor\f31513\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}{\flomajor\f31514\fbidi \froman\fcharset178\fprq2 Times New Roman (Arabic);}{\flomajor\f31515\fbidi \froman\fcharset186\fprq2 Times New Roman Baltic;}
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RF_Regressor.rtf

@@ -0,0 +1,465 @@
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+\par 
+\par       "session_info" : \{
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+\par         "experiment_id": "kkkk-11",
+\par         "dataset":"iris_modified.csv",
+\par         "session_name": "test",
+\par         "session_description": "test"
+\par         \},
+\par 
+\par       "target": \{
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+\par         "target": "species",
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+\par       \},
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+\par       \},
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+\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         \},
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+\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": \{
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+\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": \{
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+\par           "is_selected": false,
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+\par           "min_samples_per_leaf_min_value": 5,
+\par           "min_samples_per_leaf_max_value": 50,
+\par           "parallelism": 0
+\par         \},
+\par         "RandomForestRegressor": \{
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+\par           "is_selected": false,
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+\par           "max_trees": 20,
+\par           "feature_sampling_statergy": "Default",
+\par           "min_depth": 20,
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+\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": \{
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+\par           "min_iter":30,
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+\par         \},
+\par         "LassoRegression": \{
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+\par           "min_iter":30,
+\par           "max_iter":50,
+\par           "min_regparam":0.5,
+\par           "max_regparam":0.8
+\par         \},
+\par         "ElasticNetRegression": \{
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+\par           "is_selected": false,
+\par           "regularization_term": "Specify values to test",
+\par           "min_iter":30,
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+\par           "max_elasticnet":0.8
+\par         \},
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+\par           "is_selected": false,
+\par           "use_gradient_boosted_tree": true,
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SVM.rtf

@@ -0,0 +1,465 @@
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XG_Boost.rtf

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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": \{
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