genelens.fselector

module documentation

Machine learning pipeline for biomarker discovery

Class FeatureSelector Feature selection using regularized logistic regression with automatic C parameter tuning.
Class fsplot Implementation of graphics methods for FeatureSelector module logs
Function get_feature_space the function returns a set of FeatureSelector models that satisfy the condition
Function train_test_split_res train test split with resampling
Function _count_min_class Undocumented
def get_feature_space(model_list, cut_off_level=0.25):

the function returns a set of FeatureSelector models that satisfy the condition

def train_test_split_res(X, y, feature_resample=0):

train test split with resampling Attributes: ----- X : array-like or pd.DataFrame Feature matrix (n_samples, n_features) y : array-like Binary target vector (n_samples,) feature_resample: int, optional (default=0) Resampling of features. If 0, the full feature space is considered at each train_test_split, otherwise the feature space is also sampled in batches of size "feature_resample"

def _count_min_class(vector):

Undocumented