From 3a9c9332b660d35720ad4fa1f55ee0883e53aecd Mon Sep 17 00:00:00 2001 From: "helma@in-silico.ch" Date: Fri, 2 Nov 2018 20:34:44 +0100 Subject: warnings fixed, cleanup --- test/classification-validation.rb | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) (limited to 'test/classification-validation.rb') diff --git a/test/classification-validation.rb b/test/classification-validation.rb index 85db8ba..302b2c8 100644 --- a/test/classification-validation.rb +++ b/test/classification-validation.rb @@ -1,12 +1,13 @@ require_relative "setup.rb" -class ValidationClassificationTest < MiniTest::Test +class ClassificationValidationTest < MiniTest::Test include OpenTox::Validation # defaults def test_default_classification_crossvalidation - dataset = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv" + #dataset = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv" + dataset = Dataset.from_csv_file "#{DATA_DIR}/multi_cell_call.csv" model = Model::Lazar.create training_dataset: dataset cv = ClassificationCrossValidation.create model assert cv.accuracy[:without_warnings] > 0.65, "Accuracy (#{cv.accuracy[:without_warnings]}) should be larger than 0.65, this may occur due to an unfavorable training/test set split" @@ -45,7 +46,6 @@ class ValidationClassificationTest < MiniTest::Test dataset = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv" model = Model::Lazar.create training_dataset: dataset loo = ClassificationLeaveOneOut.create model - assert_equal 77, loo.nr_unpredicted refute_empty loo.confusion_matrix assert loo.accuracy[:without_warnings] > 0.650 assert loo.weighted_accuracy[:all] > loo.accuracy[:all], "Weighted accuracy (#{loo.weighted_accuracy[:all]}) should be larger than accuracy (#{loo.accuracy[:all]})." -- cgit v1.2.3