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# encoding: utf-8
require File.dirname(__FILE__) + '/../test_helper'
class BayesianTest < Minitest::Test
def setup
@classifier = ClassifierReborn::Bayes.new 'Interesting', 'Uninteresting'
end
def test_good_training
assert_equal ['love'], @classifier.train_interesting('love')
end
def test_training_with_utf8
assert_equal ['Água'], @classifier.train_interesting('Água')
end
def test_stemming_enabled_by_default
assert @classifier.stemmer_enabled?
end
def test_bad_training
assert_raises(StandardError) { @classifier.train_no_category 'words' }
end
def test_bad_method
assert_raises(NoMethodError) { @classifier.forget_everything_you_know '' }
end
def test_categories
assert_equal %w(Interesting Uninteresting).sort, @classifier.categories.sort
end
def test_categories_from_array
another_classifier = ClassifierReborn::Bayes.new %w(Interesting Uninteresting)
assert_equal another_classifier.categories.sort, @classifier.categories.sort
end
def test_add_category
@classifier.add_category 'Test'
assert_equal %w(Test Interesting Uninteresting).sort, @classifier.categories.sort
end
def test_dynamic_category_succeeds_with_auto_categorize
classifier = ClassifierReborn::Bayes.new 'Interesting', 'Uninteresting', auto_categorize: true
classifier.train('Ruby', 'I really sweet language')
assert classifier.categories.include?('Ruby')
end
def test_dynamic_category_fails_without_auto_categorize
assert_raises(ClassifierReborn::Bayes::CategoryNotFoundError) do
@classifier.train('Ruby', 'A really sweet language')
end
refute @classifier.categories.include?('Ruby')
end
def test_classification
@classifier.train_interesting 'here are some good words. I hope you love them'
@classifier.train_uninteresting 'here are some bad words, I hate you'
assert_equal 'Uninteresting', @classifier.classify('I hate bad words and you')
end
def test_classification_with_threshold
b = ClassifierReborn::Bayes.new 'Digit'
assert_equal 1, b.categories.size
refute b.threshold_enabled?
b.enable_threshold
assert b.threshold_enabled?
assert_equal 0.0, b.threshold # default
b.threshold = -7.0
10.times do |a_number|
b.train_digit(a_number.to_s)
b.train_digit(a_number.to_s)
end
10.times do |a_number|
assert_equal 'Digit', b.classify(a_number.to_s)
end
refute b.classify('xyzzy')
end
def test_classification_with_threshold_again
b = ClassifierReborn::Bayes.new 'Normal'
assert_equal 1, b.categories.size
refute b.threshold_enabled?
b.enable_threshold
assert b.threshold_enabled?
assert_equal 0.0, b.threshold # default
%w(
http://example.com/about
http://example.com/contact
http://example.com/download
http://example.com/login
http://example.com/logout
http://example.com/blog/2015-04-01
).each do |url|
b.train_normal(url)
end
assert 'Normal', b.classify('http://example.com')
refute b.classify("http://example.com/login/?user='select * from users;'")
end
def test_classification_with_score
@classifier.train_interesting 'here are some good words. I hope you love them'
@classifier.train_uninteresting 'here are some bad words, I hate you'
assert_in_delta(-4.85, @classifier.classify_with_score('I hate bad words and you')[1], 0.1)
end
def test_untrain
@classifier.train_interesting 'here are some good words. I hope you love them'
@classifier.train_uninteresting 'here are some bad words, I hate you'
@classifier.add_category 'colors'
@classifier.train_colors 'red orange green blue seven'
classification_of_bad_data = @classifier.classify 'seven'
@classifier.untrain_colors 'seven'
classification_after_untrain = @classifier.classify 'seven'
refute_equal classification_of_bad_data, classification_after_untrain
end
end
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