ayanatherate

import numpy as np
from scipy import stats

def pearsonr_ci(x,y,alpha=0.05):
    ''' calculate Pearson correlation along with the confidence interval using scipy and numpy

    Parameters
    ----------
    x, y : iterable object such as a list or np.array
      Input for correlation calculation

MLWhiz

from sklearn.feature_selection import RFE
from sklearn.linear_model import LogisticRegression
rfe_selector = RFE(estimator=LogisticRegression(), n_features_to_select=num_feats, step=10, verbose=5)
rfe_selector.fit(X_norm, y)
rfe_support = rfe_selector.get_support()
rfe_feature = X.loc[:,rfe_support].columns.tolist()
print(str(len(rfe_feature)), 'selected features')