Ensemble Methods

Adaboost, Bagging, ExtraTrees, GradientBoosting, GradientBoosting, Isolation Forest, Random Forest, Stacking, Voting, HistGradientBoosting

AdaBoost, Bagging

For both Classifier & Regressor

Input Data

	Inputs
*Target Data(X)	Data Input
*Model Name	Name of the user-defined model
Predict Output	Name of the output data
Merge Data	Predict Output will be created with predicted labels concatenated to Merge Data.
*X	User-selected columns to be X.
*Y	User-selected columns to be Y.

Defining estimators

In case of using AdaBoost and Bagging models, you have to define the base_estimator in Arguments.

About R-Flow estimators

[Task Information of AdaBoost Classifier/Regressor]

ExtraTrees, GradientBoosting, RandomForest, HistGradientBoosting

For both Classifier & Regressor

Input Data

	Inputs
*Target Data	Data Input
*Model Name	Name of the user-defined model
Predict Output	Name of the output data
Merge Data	Predict Output will be created with predicted labels concatenated to Merge Data.
*X	User-selected columns to be X.
*Y	User-selected columns to be Y.

[Task Information of ExtraTreeClassifier/Regressor]

IsolationForest

Input Data

	Inputs
*Target Data	Data Input
*Model Name	Name of the user-defined model
Predict Output	Name of the output data
Merge Data	Predict Output will be created with predicted labels concatenated to Merge Data.
*X	User-selected columns to be X

[Task Information of IsolationForest]

Stacking, Voting

For both classifier & regressor

Input Data

	Inputs
*Target Data(X)	Data Input
*Model Name	Name of the user-defined model
Predict Output	Name of the output data
Merge Data	Predict Output will be created with predicted labels concatenated to Merge Data.
*X	User-selected columns to be X.
*Y	User-selected column to be Y.

Defining estimators

In case of using Stacking & Voting models, stack the base_estimators in Arguments.

Each element of the list is defined as a tuple of string (i.e. user-defined name of the estimator) and an estimator instance.

Define the 'estimators' in Argument as below:

[('str1', estimator1),('str2', estimator2)] (ex. [('rf', RF),('gdb',GDB),('adb',ADB)] )

[example of StackingClassifier estimators]

Example Workflow

R-Flow Task Example Video- StackingClassifier

[Example of Stacking Classifier]

Python Package

AdaBoostClassifier: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostClassifier.html

AdaBoostRegressor: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostRegressor.html

BaggingClassifier: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingClassifier.html

BaggingRegressor: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingRegressor.html

ExtraTreesClassifier: https://scikit-learn.org/0.15/modules/generated/sklearn.ensemble.ExtraTreesClassifier.html

ExtraTreeRegressor: https://scikit-learn.org/0.15/modules/generated/sklearn.ensemble.ExtraTreesRegressor.html

GradientBoostingClassifier: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html

GradientBoostingRegressor: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html

IsolationForest: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html

RandomForestClassifier: http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html

RandomForestRegressor: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html

StackingClassifier: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingClassifier.html

StackingRegressor: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingRegressor.html

VotingClassifier: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingClassifier.html

VotingRegressor: https://scikit-learn.org/0.22/modules/generated/sklearn.ensemble.VotingRegressor.html

HistGradientBoostingClassifier: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html

HistGradientBoostingRegressor: https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html