AutoML_With_Json / Linear.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
\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": \{
\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": true,
\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,
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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": \{
\par "model_name": "XG Boost",
\par "is_selected": false,
\par "use_gradient_boosted_tree": true,
\par "dart": true,
\par "tree_method": "",
\par "random_state": 0,
\par "max_num_of_trees": 0,
\par "early_stopping": true,
\par "early_stopping_rounds": 2,
\par "max_depth_of_tree": [56, 89],
\par "learningRate": [89, 76],
\par "l1_regularization": [77],
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