ClassifierModels: Run a set of classification models on input training, test...

In mattdneal/FAIMSToolkit: Tools to aid in the analysis of FAIMS data

Description

Run a set of classification models on input training, test data sets

Usage

ClassifierModels(data.train, targetValues, data.test, models, kFolds = 2,
  repeats = 5, tuneLength = 5, verbose = F)

Arguments

data.train	a data frame of training data
targetValues	a logical vector
data.test	a data frame of test data (columns must match data.train)
models	a list of caret::train models to run
kFolds	number of folds for model selection within each fold
repeats	number of repeats for model selection within each fold
tuneLength	number of parameters to tune
verbose	verbose output if TRUE

Value

a data frame containing prediction probabilities for each classification algorithm. These are the predicted probabililty of targetValues==TRUE

mattdneal/FAIMSToolkit documentation built on May 21, 2019, 12:57 p.m.