///|
fn main {
  let data = @svm.dataset(
    [
      [-3.0, -3.0],
      [-2.0, -3.0],
      [-3.0, -2.0],
      [0.0, 3.0],
      [1.0, 3.0],
      [0.0, 4.0],
      [3.0, -2.0],
      [4.0, -2.0],
      [3.0, -1.0],
    ],
    [10, 10, 10, 20, 20, 20, 30, 30, 30],
    "multiclass example",
  ).unwrap()
  let config = @svm.default_binary_config(@svm.Linear).unwrap()
  let model = @svm.train_multiclass(data, config).unwrap()
  let explanation = @svm.explain_multiclass_prediction(model, [0.0, 3.5]).unwrap()
  println("class_count=\{explanation.classes().length()}")
  for index, score in explanation.scores() {
    println("score_\{index}=\{score}")
  }
  println("prediction=\{explanation.predicted_class()}")
}