RF_Pred_Multiclass: Predict multiclass variables based on a taxa read count table...

In wdl2459/ConQuR: Batch Effects Removal for Microbiome Data in Large-Scale Epidemiology Studies via Conditional Quantile Regression

Predict multiclass variables based on a taxa read count table by random forest

Description

Predict multiclass variables based on a taxa read count table by random forest

Usage

RF_Pred_Multiclass(TAX, factor, fold = 5, seed = 2020)

Arguments

TAX	The taxa read count table, samples (row) by taxa (col).
factor	The multiclass variable to predict, e.g., the key variable, never smoker/former smoker/current smoker, must be a factor.
fold	The number of folds; default is 5.
seed	The seed to generate fold indices for samples; default is 2020.

Value

A list

• pred - A table summarizing the predicted probabilities and true labels for all samples.

• cross_entropy_across_fold - mean cross-entropy across folds.

wdl2459/ConQuR documentation built on Aug. 28, 2022, 6:08 a.m.