Train a Classifier — ls_train_classifier • libscanR

Trains SVM or Random Forest on spectral intensity features.

Usage

ls_train_classifier(dataset, grouping, method = "svm", ...)

Arguments

dataset: A ls_dataset() with labelled samples.
grouping: Character. Column name in sample_info with class labels.
method: Character. "svm" or "rf". Default "svm".
...: Additional arguments passed to the underlying trainer.

Value

An S3 object of class libs_classifier.

Examples

ds <- ls_example_data("tissue")
# \donttest{
if (requireNamespace("e1071", quietly = TRUE)) {
  clf <- ls_train_classifier(ds, "tissue", method = "svm")
  clf$accuracy
}
#> [1] 0.62
# }