Description
Measurement Level Independent Feature Correlation Matrix.
Description
Uses three different correlation coefficients to calculate measurement-level adequate correlations in a feature matrix: Pearson product-moment correlation coefficient, Intraclass correlation and Cramer's V.
README.md
featureMatrix
R package Feature Correlation Matrix
Status: First version (0.4.0) ready to get pushed to CRAN, minor changes under development already !
Authors: Dr. Guido Möser/ Ilja Muhl (in alphabetical order)
Notes: If you want to run the featureMatrix()-function, the two other functions, cv.test() and icc(), have to be available!
What it does: Estimates the correlation between categorical and numerical features (and the target variable)
Parameter:
- both variables numerical: Product-Moment-Correlation by Bravais-Pearson
- both variables categorical: Cramer's V (based on the Chi²-Test of Independence)
- one variable categorical and the other numerical: ICC (Intra-Class-Correlation) based on classical ANOVA by Fisher.