modScale: Scale Data by Factor Range

In exprso: Rapid Deployment of Machine Learning Algorithms

Description

modScale scales a data set by making all sample vectors have the same total sum, then multiplying each sample vector by a scale factor.

Usage

modScale(object, alpha = 0, uniform = TRUE)

Arguments

object	An ExprsArray object. The object that should undergo a replication of some feature selection and dimension reduction history.
alpha	An integer. The maximum range of scale factors used for scaling if uniform = TRUE. The standard deviation of the scale factors if uniform = FALSE. See Details.
uniform	A boolean. Toggles whether to draw scale factors from a uniform distribution or a normal distribution.

Details

If uniform = TRUE, scale factors are randomly sampled from the uniform distribution (0, alpha) + 1. Otherwise, scale factors are randomly sampled from the normal distribution with a mean of 0 and standard deviation of alpha. When using the normal distribution, these scale factors are transformed by taking the absolute value then adding one. For this reason, data are always unscaled when alpha = 0.

Value

A pre-processed ExprsArray object.

exprso documentation built on May 1, 2019, 7:11 p.m.