CV: CV

In mRcSchwering/abacus: abacus

Description

This function trains a shrinkage discriminant analysis (sda) classifier as in Training in a k-fold cross validation. A data.frame with class labels and predictions is returned which can be used for prediction power estimation.

Usage

CV(abt, feats, labs, k = 5, ...)

Arguments

abt	num matrix containing training data with rows as observations and columns as features
feats	data.frame with columns name and value which identifies the features (columns) of abt with chr values
labs	vector defining class labels of rows in training data
...	arguments passed to link{Training}

Value

data.frame with class labels and predictions by the classifier

See Also

Other machine learning: Convert, FeatureExtraction, Prediction, Training

Examples

abt1 <- matrix(sample(0:1, 1000*100, replace = TRUE), 1000, 100)
feats1 <- data.frame(name = "test", value = 1:100)
labs1 <- sample(0:1, 1000, replace = TRUE)
err <- CV(abt1, feats1, labs1)
(acc <- sum(err$class == err$prediction) / nrow(err) * 100)

mRcSchwering/abacus documentation built on May 21, 2019, 9:18 a.m.