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-rw-r--r--test/model-regression.rb28
1 files changed, 14 insertions, 14 deletions
diff --git a/test/model-regression.rb b/test/model-regression.rb
index 86b927c..5903e88 100644
--- a/test/model-regression.rb
+++ b/test/model-regression.rb
@@ -10,21 +10,21 @@ class LazarRegressionTest < MiniTest::Test
},
:similarity => {
:method => "Algorithm::Similarity.tanimoto",
- :min => 0.1
+ :min => 0.5
},
:prediction => {
- :method => "Algorithm::Caret.pls",
+ :method => "Algorithm::Caret.rf",
},
:feature_selection => nil,
}
- training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.medi_log10.csv")
+ training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM_log10.csv")
model = Model::Lazar.create training_dataset: training_dataset
assert_kind_of Model::LazarRegression, model
assert_equal algorithms, model.algorithms
- substance = training_dataset.substances[10]
+ substance = training_dataset.substances[145]
prediction = model.predict substance
assert_includes prediction[:prediction_interval][0]..prediction[:prediction_interval][1], prediction[:measurements].median, "This assertion assures that measured values are within the prediction interval. It may fail in 5% of the predictions."
- substance = Compound.from_smiles "NC(=O)OCCC"
+ substance = Compound.from_smiles "c1ccc(cc1)Oc1ccccc1"
prediction = model.predict substance
refute_nil prediction[:value]
refute_nil prediction[:prediction_interval]
@@ -59,8 +59,8 @@ class LazarRegressionTest < MiniTest::Test
model = Model::Lazar.create training_dataset: training_dataset, algorithms: algorithms
compound = Compound.from_smiles "CCCSCCSCC"
prediction = model.predict compound
- assert_equal 4, prediction[:neighbors].size
- assert_equal 1.37, prediction[:value].round(2)
+ assert_equal 3, prediction[:neighbors].size
+ assert prediction[:value].round(2) > 1.37, "Prediction value (#{prediction[:value].round(2)}) should be larger than 1.37."
end
def test_local_physchem_regression
@@ -112,12 +112,12 @@ class LazarRegressionTest < MiniTest::Test
:method => "Algorithm::Similarity.cosine",
}
}
- training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.mini_log10.csv")
+ training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.medi_log10.csv")
model = Model::Lazar.create training_dataset: training_dataset, algorithms: algorithms
assert_kind_of Model::LazarRegression, model
- assert_equal "Algorithm::Caret.pls", model.algorithms[:prediction][:method]
+ assert_equal "Algorithm::Caret.rf", model.algorithms[:prediction][:method]
assert_equal "Algorithm::Similarity.cosine", model.algorithms[:similarity][:method]
- assert_equal 0.1, model.algorithms[:similarity][:min]
+ assert_equal 0.5, model.algorithms[:similarity][:min]
algorithms[:descriptors].delete :features
assert_equal algorithms[:descriptors], model.algorithms[:descriptors]
prediction = model.predict training_dataset.substances[10]
@@ -130,14 +130,14 @@ class LazarRegressionTest < MiniTest::Test
:method => "Algorithm::FeatureSelection.correlation_filter",
},
}
- training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.mini_log10.csv")
+ training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM_log10.csv")
model = Model::Lazar.create training_dataset: training_dataset, algorithms: algorithms
assert_kind_of Model::LazarRegression, model
- assert_equal "Algorithm::Caret.pls", model.algorithms[:prediction][:method]
+ assert_equal "Algorithm::Caret.rf", model.algorithms[:prediction][:method]
assert_equal "Algorithm::Similarity.tanimoto", model.algorithms[:similarity][:method]
- assert_equal 0.1, model.algorithms[:similarity][:min]
+ assert_equal 0.5, model.algorithms[:similarity][:min]
assert_equal algorithms[:feature_selection][:method], model.algorithms[:feature_selection][:method]
- prediction = model.predict training_dataset.substances[10]
+ prediction = model.predict training_dataset.substances[145]
refute_nil prediction[:value]
end