flâneur

sklearn.feature_selection.RFE — scikit-learn 1.3.0 documentation

scikit-learn.org · 1,759 words · saved by 1 readers

Examples using sklearn.feature_selection.RFE: Recursive feature elimination

RFE # class sklearn.feature_selection. RFE ( estimator , * , n_features_to_select = None , step = 1 , verbose = 0 , importance_getter = 'auto' ) [source] # Feature ranking with recursive feature elimination. Given an external estimator that assigns weights to features (e.g., the coefficients of a linear model), the goal of recursive feature elimination (RFE) is to select features by recursively considering smaller and smaller sets of features. First, the estimator is trained on the initial set of features and the importance of each feature is obtained either through any specific attribute or c

saved by

related reading