generate_pi_histogram: Generate pi Histogram Plot

In tkolisnik/Rf2pval: A comprehensive approach to genomic analysis using scikit-learn's Random Forest models and rank-based feature reduction in R

Generate pi Histogram Plot

Description

Creates a histogram showing the sum of absolute deviations by count, the measures used to calculate the pi statistics used in the p-value calculation for the set.

Usage

generate_pi_histogram(permutedvalues, quantiledata)

Arguments

permutedvalues	a tibble of feature ranks, feature names, feature importance scores, log feature importance scores and permutation # generated by the load_permuted_fws function
quantiledata	a tibble containing: feature ranks, mean, lower, upper, and observed as well as logmean, loglower, logupper, logobserved generated by the calculateQuantiles function

Details

This function generates a histogram illustrating the sum of absolute deviations in the permuted set vs the true (observed) set. It is a visualization of the data used to calculate the p-value for the entire feature set.

Value

A histogram of count by sum of absolute deviations, showing the differences between the null and observed datasets.

Examples

pihist_plot<-generate_pi_histogram(feat_importances$permuted_importances, quantile_data)

tkolisnik/Rf2pval documentation built on Feb. 20, 2024, 5:39 a.m.