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Overview

Description

These techniques employ statistical methods to rank features according to their correlation with the target variable. Common methods encompass chi-squared, mutual information, and correlation coefficients. Features are subsequently chosen based on a predefined threshold.

Filter methods describe a type of data that consists of observations on only a single characteristic or attribute.

Filter methods examine each feature individually to determine the strength of the relationship of the feature with the response variable.

Some examples of statistical tests that can be used to evaluate feature relevance are:

  • Pearson Correlation
  • Maximal information coefficient
  • Distance correlation
  • ANOVA
  • Chi-square