MASTMLFeatureSelector¶
- class mastml.feature_selectors.MASTMLFeatureSelector(model, n_features_to_select, cv=None, manually_selected_features=[])[source]¶
Bases:
BaseSelector
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[, Xgroups])transform
(X)Methods Documentation