feature_prevalence: Feature prevalence

In iteremoval: Iteration removal method for feature selection

Description

Compute the feature prevalence after removing the features of the first index iterations.

Usage

feature_prevalence(li, index, hist.plot = TRUE)

Arguments

li	the list result of feature_removal.
index	removing the features of the first index iterations. It allows a positive integer or a proper fraction. If inproper fraction, it is regarded as as.integer(index).
hist.plot	bool. A switch to plot the histogram of the remaining features.

Value

Matrix

Examples

g1 <- SWRG1; g0 <- SWRG0

result.complex <- feature_removal(g1, g0,
    cutoff1=0.95, cutoff0=0.925,
    offset=c(0.5, 1, 2))

# index is a proportion in 0-1
prevalence.result <- feature_prevalence(result.complex, 0.5, hist.plot=TRUE)

# index is a positive integer
prevalence.result <- feature_prevalence(result.complex, 233, hist.plot=TRUE)

iteremoval documentation built on Nov. 8, 2020, 11:12 p.m.