lib/svmkit/ensemble/ada_boost_classifier.rb in svmkit-0.7.2 vs lib/svmkit/ensemble/ada_boost_classifier.rb in svmkit-0.7.3

@@ -107,10 +107,10 @@
           ids = SVMKit::Utils.choice_ids(n_samples, observation_weights, @rng)
           break if y[ids].to_a.uniq.size != n_classes
           tree = Tree::DecisionTreeClassifier.new(
             criterion: @params[:criterion], max_depth: @params[:max_depth],
             max_leaf_nodes: @params[:max_leaf_nodes], min_samples_leaf: @params[:min_samples_leaf],
-            max_features: @params[:max_features], random_seed: @rng.rand(SVMKit::Values::int_max)
+            max_features: @params[:max_features], random_seed: @rng.rand(SVMKit::Values.int_max)
           )
           tree.fit(x[ids, true], y[ids])
           # Calculate estimator error.
           proba = tree.predict_proba(x).clip(1.0e-15, nil)
           p = Numo::Int32.asarray(Array.new(n_samples) { |n| @classes[proba[n, true].max_index] })