extra_trees_regressor.rb in rumale-0.14.3

- old
+ new

@@ -40,11 +40,11 @@
       #   If nil is given, extra tree grows without concern for depth.
       # @param max_leaf_nodes [Integer] The maximum number of leaves on extra tree.
       #   If nil is given, number of leaves is not limited.
       # @param min_samples_leaf [Integer] The minimum number of samples at a leaf node.
       # @param max_features [Integer] The number of features to consider when searching optimal split point.
-      #   If nil is given, split process considers all features.
+      #   If nil is given, split process considers 'Math.sqrt(n_features)' features.
       # @param n_jobs [Integer] The number of jobs for running the fit and predict methods in parallel.
       #   If nil is given, the methods do not execute in parallel.
       #   If zero or less is given, it becomes equal to the number of processors.
       #   This parameter is ignored if the Parallel gem is not loaded.
       # @param random_seed [Integer] The seed value using to initialize the random generator.
@@ -71,10 +71,10 @@
         x = check_convert_sample_array(x)
         y = check_convert_tvalue_array(y)
         check_sample_tvalue_size(x, y)
         # Initialize some variables.
         n_features = x.shape[1]
-        @params[:max_features] = Math.sqrt(n_features).to_i unless @params[:max_features].is_a?(Integer)
+        @params[:max_features] = Math.sqrt(n_features).to_i if @params[:max_features].nil?
         @params[:max_features] = [[1, @params[:max_features]].max, n_features].min
         sub_rng = @rng.dup
         # Construct forest.
         rng_seeds = Array.new(@params[:n_estimators]) { sub_rng.rand(Rumale::Values.int_max) }
         @estimators = if enable_parallel?