MASTMLFeatureSelector

class mastml.legos.feature_selectors.MASTMLFeatureSelector(estimator, n_features_to_select, cv, manually_selected_features=[])

Bases: object

Class custom-written for MAST-ML to conduct forward selection of features with flexible model and cv scheme

Args:

estimator: (scikit-learn model/estimator object), a scikit-learn model/estimator

n_features_to_select: (int), the number of features to select

cv: (scikit-learn cross-validation object), a scikit-learn cross-validation object

manually_selected_features: (list), a list of features manually set by the user. The feature selector will first start from this list of features and sequentially add features until n_features_to_select is met.

Methods:

fit: performs feature selection

Args:

X: (dataframe), dataframe of X features

y: (dataframe), dataframe of y data

Xgroups: (dataframe), dataframe of group labels

Returns:

None

transform: performs the transform to generate output of only selected features

Args:

X: (dataframe), dataframe of X features

Returns:

dataframe: (dataframe), dataframe of selected X features

Methods Summary

fit(X, y, savepath[, Xgroups])
transform(X)

Methods Documentation

fit(X, y, savepath, Xgroups=None)

transform(X)