Classify Unknown Spectra

Applies a trained classifier (from ls_plsda() or ls_train_classifier()) to new spectra.

Usage

ls_classify(model, new_data)

Arguments

model

A libs_plsda or libs_classifier object.

new_data

A ls_dataset() of unknown spectra.

Value

A tibble::tibble() with columns sample_id, predicted_class, and optionally probability.

Examples

ds <- ls_example_data("tissue")
# \donttest{
if (requireNamespace("e1071", quietly = TRUE)) {
  clf <- ls_train_classifier(ds[1:30], "tissue", method = "svm")
  ls_classify(clf, ds[31:50])
}
#> # A tibble: 20 × 3
#>    sample_id predicted_class probability
#>    <chr>     <chr>                 <dbl>
#>  1 muscle_01 kidney                0.539
#>  2 muscle_02 kidney                0.519
#>  3 muscle_03 liver                 0.544
#>  4 muscle_04 kidney                0.564
#>  5 muscle_05 kidney                0.565
#>  6 muscle_06 kidney                0.569
#>  7 muscle_07 liver                 0.581
#>  8 muscle_08 liver                 0.548
#>  9 muscle_09 liver                 0.489
#> 10 muscle_10 kidney                0.554
#> 11 fat_01    liver                 0.548
#> 12 fat_02    kidney                0.560
#> 13 fat_03    kidney                0.545
#> 14 fat_04    kidney                0.566
#> 15 fat_05    liver                 0.559
#> 16 fat_06    kidney                0.552
#> 17 fat_07    liver                 0.587
#> 18 fat_08    liver                 0.588
#> 19 fat_09    liver                 0.551
#> 20 fat_10    liver                 0.562
# }