OpenBabel can (canonical smiles) instead of inchi as internal identifier to avoid OpenBabel InChi bug.

1 files changed, 41 insertions, 0 deletions

diff --git a/test/validation.rb b/test/validation.rb
new file mode 100644
index 0000000..d98feb5
--- /dev/null
+++ b/test/validation.rb
@@ -0,0 +1,41 @@
+require_relative "setup.rb"
+
+class ValidationTest < MiniTest::Test
+
+  def test_fminer_crossvalidation
+    dataset = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv"
+    model = Model::LazarFminerClassification.create dataset#, features
+    cv = ClassificationCrossValidation.create model
+    p cv.accuracy
+    p cv.weighted_accuracy
+    assert cv.accuracy > 0.8
+    assert cv.weighted_accuracy > cv.accuracy, "Weighted accuracy (#{cv.weighted_accuracy}) larger than unweighted accuracy(#{cv.accuracy}) "
+  end
+
+  def test_classification_crossvalidation
+    dataset = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv"
+    model = Model::LazarClassification.create dataset#, features
+    cv = ClassificationCrossValidation.create model
+    p cv.accuracy
+    p cv.weighted_accuracy
+    assert cv.accuracy > 0.7
+    assert cv.weighted_accuracy > cv.accuracy, "Weighted accuracy should be larger than unweighted accuracy."
+  end
+
+  def test_regression_crossvalidation
+    dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi.csv"
+    #dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.csv"
+    model = Model::LazarRegression.create dataset
+    cv = RegressionCrossValidation.create model
+    p cv.rmse 
+    p cv.weighted_rmse
+    p cv.mae
+    p cv.weighted_mae
+    `inkview #{cv.plot}`
+    assert cv.rmse < 30, "RMSE > 30"
+    assert cv.weighted_rmse < cv.rmse, "Weighted RMSE (#{cv.weighted_rmse}) larger than unweighted RMSE(#{cv.rmse}) "
+    assert cv.mae < 12
+    assert cv.weighted_mae < cv.mae
+  end
+
+end