get_best_predictions: Get best predictions

In jonathanth/mixOmicsCaret: mixOmicsCaret

Get best predictions

Description

Returns the CV predictions associated with the best performing tuning parameters. If there are multiple CV repeats, these are separated.

Usage

get_best_predictions(trainobj, rep = NA, ncomp = NA, keepX = NA,
  keepY = NA)

Arguments

trainobj	The train object from caret, fit using mixOmics spls.
rep	If trainobj was fit using repeated cross-validation, choose a repeat (e.g. "Rep1") or leave as NA for all repeats (default).
ncomp	Manually select CV predictions with this parameter, instead of the best one from train.
keepX	Manually select CV predictions with this parameter, instead of the best one from train.
keepY	Manually select CV predictions with this parameter, instead of the best one from train.

Value

A data.frame with the variables

• pred - the predicted values

• obs - the observed values

• ncomp - Tuning variable

• keepX - Tuning variable

• keepY - Tuning variable

• fold - Cross-validation fold

• rep - Repeat number (for repeated CV)

Examples

library(caret)
x <- data.frame(matrix(rnorm(1000),nrow = 100))
y <- rnorm(100)
PLS <- train(x = x, y = y, method = get_mixOmics_spls())
getBestPredictions(PLS)

jonathanth/mixOmicsCaret documentation built on Feb. 25, 2023, 5:41 a.m.