test/classifiers/naive_bayes_test.rb in ai4r-1.12 vs test/classifiers/naive_bayes_test.rb in ai4r-1.13

- old
+ new

@@ -5,39 +5,39 @@ include Ai4r::Classifiers include Ai4r::Data class NaiveBayesTest < Test::Unit::TestCase - @@data_labels = [ "Color","Type","Origin","Stolen?" ] + @@data_labels = %w(Color Type Origin Stolen?) @@data_items = [ - ["Red", "Sports", "Domestic", "Yes"], - ["Red", "Sports", "Domestic", "No"], - ["Red", "Sports", "Domestic", "Yes"], - ["Yellow","Sports", "Domestic", "No"], - ["Yellow","Sports", "Imported", "Yes"], - ["Yellow","SUV", "Imported", "No"], - ["Yellow","SUV", "Imported", "Yes"], - ["Yellow","Sports", "Domestic", "No"], - ["Red", "SUV", "Imported", "No"], - ["Red", "Sports", "Imported", "Yes"] - ] + %w(Red Sports Domestic Yes), + %w(Red Sports Domestic No), + %w(Red Sports Domestic Yes), + %w(Yellow Sports Domestic No), + %w(Yellow Sports Imported Yes), + %w(Yellow SUV Imported No), + %w(Yellow SUV Imported Yes), + %w(Yellow Sports Domestic No), + %w(Red SUV Imported No), + %w(Red Sports Imported Yes) + ] def setup @data_set = DataSet.new @data_set = DataSet.new(:data_items => @@data_items, :data_labels => @@data_labels) - @b = NaiveBayes.new.set_parameters({:m=>3}).build @data_set + @b = NaiveBayes.new.set_parameters({:m => 3}).build @data_set end def test_eval - result = @b.eval(["Red", "SUV", "Domestic"]) - assert_equal "No", result + result = @b.eval(%w(Red SUV Domestic)) + assert_equal 'No', result end def test_get_probability_map - map = @b.get_probability_map(["Red", "SUV", "Domestic"]) + map = @b.get_probability_map(%w(Red SUV Domestic)) assert_equal 2, map.keys.length - assert_in_delta 0.42, map["Yes"], 0.1 - assert_in_delta 0.58, map["No"], 0.1 + assert_in_delta 0.42, map['Yes'], 0.1 + assert_in_delta 0.58, map['No'], 0.1 end end