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

@@ -109,10 +109,10 @@
           # Fit weak learner.
           ids = SVMKit::Utils.choice_ids(n_samples, observation_weights, @rng)
           tree = Tree::DecisionTreeRegressor.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])
           p = tree.predict(x)
           # Calculate errors.
           abs_err = ((p - y) / y).abs