SVM Pixel Classification — hs_classify

Trains a Support Vector Machine on labeled pixels and classifies all pixels. Requires the e1071 package.

Usage

hs_classify_svm(
  cube,
  training_labels,
  training_mask = NULL,
  kernel = "radial",
  cost = 10,
  gamma = NULL,
  ...
)

Arguments

cube: An hsi_cube object.
training_labels: Character or factor matrix (same spatial dims as cube) with class labels. NA for unlabeled pixels.
training_mask: Logical matrix. Alternative to NA in labels. Default NULL.
kernel: Character. SVM kernel: "radial" (default), "linear", "polynomial".
cost: Numeric. Cost parameter. Default 10.
gamma: Numeric. Gamma parameter. Default NULL (auto).
...: Additional arguments passed to e1071::svm().

Value

A list with class "hsi_classification" containing class_map.

Examples

# \donttest{
# Requires e1071 package
cube <- hs_example_cube()
labels <- matrix(NA_character_, 30, 30)
labels[1:10, 1:10] <- "class_a"
labels[20:30, 20:30] <- "class_b"
if (requireNamespace("e1071", quietly = TRUE)) {
  result <- hs_classify_svm(cube, labels)
}
# }