Source code for moosefs.feature_selectors.variance_selectors

import numpy as np
import pandas as pd
from .base_selector import FeatureSelector




class VarianceSelector(FeatureSelector):
    name = "Variance"



    def __init__(self, task: str, num_features_to_select: int, **kwargs):
        super().__init__(task, num_features_to_select)




    def compute_scores(self, X, y):
        if isinstance(X, np.ndarray):
            X = pd.DataFrame(X, columns=[f"feature_{i}" for i in range(X.shape[1])])
        return X.var(ddof=0).values  # base class will keep the highest variances