From 0882c2cd0de934d7377fc9d08c306be98612c88a Mon Sep 17 00:00:00 2001 From: "helma@in-silico.ch" Date: Fri, 16 Nov 2018 18:42:42 +0100 Subject: real datasets for testing, test data cleanup, Daphnia import, upper and lower similarity thresholds --- test/classification-model.rb | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) (limited to 'test/classification-model.rb') diff --git a/test/classification-model.rb b/test/classification-model.rb index 1a3d4a8..8cbd4bb 100644 --- a/test/classification-model.rb +++ b/test/classification-model.rb @@ -10,7 +10,7 @@ class ClassificationModelTest < MiniTest::Test }, :similarity => { :method => "Algorithm::Similarity.tanimoto", - :min => 0.5 + :min => [0.5,0.2] }, :prediction => { :method => "Algorithm::Classification.weighted_majority_vote", @@ -61,7 +61,7 @@ class ClassificationModelTest < MiniTest::Test :type => "MACCS" }, :similarity => { - :min => 0.4 + :min => [0.4,0.1] }, } training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"hamster_carcinogenicity.csv") @@ -77,7 +77,7 @@ class ClassificationModelTest < MiniTest::Test end def test_dataset_prediction - training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"multi_cell_call.csv") + training_dataset = Dataset.from_csv_file File.join(Download::DATA,"Carcinogenicity-Rodents.csv") test_dataset = Dataset.from_csv_file File.join(DATA_DIR,"hamster_carcinogenicity.csv") model = Model::Lazar.create training_dataset: training_dataset result = model.predict test_dataset @@ -85,16 +85,16 @@ class ClassificationModelTest < MiniTest::Test assert_equal 7, result.features.size assert_equal 85, result.compounds.size prediction_feature = result.prediction_features.first - assert_equal ["yes"], result.values(result.compounds[1], prediction_feature) - assert_equal ["no"], result.values(result.compounds[5], prediction_feature) + assert_equal ["carcinogenic"], result.values(result.compounds[1], prediction_feature) + assert_equal ["non-carcinogenic"], result.values(result.compounds[5], prediction_feature) assert_nil result.predictions[result.compounds.first][:value] - assert_equal "yes", result.predictions[result.compounds[1]][:value] + assert_equal "carcinogenic", result.predictions[result.compounds[1]][:value] assert_equal 0.27, result.predictions[result.compounds[1]][:probabilities]["no"].round(2) end def test_carcinogenicity_rf_classification skip "Caret rf may run into a (endless?) loop for some compounds." - dataset = Dataset.from_csv_file "#{DATA_DIR}/multi_cell_call.csv" + dataset = Dataset.from_csv_file File.join(Download::DATA,"Carcinogenicity-Rodents.csv") algorithms = { :prediction => { :method => "Algorithm::Caret.rf", -- cgit v1.2.3