8.8.5. sklearn.feature_selection.SelectFwe¶
- class sklearn.feature_selection.SelectFwe(score_func, alpha=0.05)¶
- Filter: Select the p-values corresponding to Family-wise error rate - Parameters : - score_func: callable : - function taking two arrays X and y, and returning 2 arrays: both scores and pvalues - alpha: float, optional : - the highest uncorrected p-value for features to keep - Methods - fit(X, y) - Evaluate the function - fit_transform(X[, y]) - Fit to data, then transform it - get_params([deep]) - Get parameters for the estimator - get_support([indices]) - Return a mask, or list, of the features/indices selected. - inverse_transform(X) - Transform a new matrix using the selected features - set_params(**params) - Set the parameters of the estimator. - transform(X) - Transform a new matrix using the selected features - __init__(score_func, alpha=0.05)¶
 - fit(X, y)¶
- Evaluate the function 
 - fit_transform(X, y=None, **fit_params)¶
- Fit to data, then transform it - Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X. - Parameters : - X : numpy array of shape [n_samples, n_features] - Training set. - y : numpy array of shape [n_samples] - Target values. - Returns : - X_new : numpy array of shape [n_samples, n_features_new] - Transformed array. - Notes - This method just calls fit and transform consecutively, i.e., it is not an optimized implementation of fit_transform, unlike other transformers such as PCA. 
 - get_params(deep=True)¶
- Get parameters for the estimator - Parameters : - deep: boolean, optional : - If True, will return the parameters for this estimator and contained subobjects that are estimators. 
 - get_support(indices=False)¶
- Return a mask, or list, of the features/indices selected. 
 - inverse_transform(X)¶
- Transform a new matrix using the selected features 
 - set_params(**params)¶
- Set the parameters of the estimator. - The method works on simple estimators as well as on nested objects (such as pipelines). The former have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object. - Returns : - self : 
 - transform(X)¶
- Transform a new matrix using the selected features 
 
