Method: Libsvm::Model#predict_probability

Defined in:

ext/libsvm/libsvm.c

#predict_probability(example) ⇒ Array<Float, Array<Float>>

Classify an example and return both the label (or regression value), as well as the array of probability found for each class.

The first element of the returned array contains the label. The second element is another array which contains the probability value found for each model class.

Library function svm_predict_probability.

Returns:

• (Array<Float, Array<Float>>) —

  predicted label and probability per class

# File 'ext/libsvm/libsvm.c', line 383

static VALUE cModel_predict_probability(VALUE obj,VALUE example) {
  struct svm_node *x;
  struct svm_model *model;
  double class;
  double *c_estimates;
  VALUE estimates;
  VALUE target;
  int i;

  x = example_to_internal(example);
  Data_Get_Struct(obj, struct svm_model, model);
  c_estimates = calloc(model->nr_class, sizeof(double));
  if(c_estimates == 0) {
    rb_raise(rb_eNoMemError, "on predict probability estimates allocation" " %s:%i", __FILE__,__LINE__);
  }

  class = svm_predict_probability(model, x, c_estimates);

  estimates = rb_ary_new();
  for (i = 0; i < model->nr_class; i++)
    rb_ary_push(estimates, rx_from_double(c_estimates[i]));

  free(c_estimates);
  free(x);

  target = rb_ary_new();
  rb_ary_push(target, rb_float_new(class));
  rb_ary_push(target, estimates);
  return target;
}