dc045bebd58dbf547728ff2f34e1d9a0fcb916f9,test/aqua/test_svm_classical.py,TestSVMClassical,test_classical_multiclass_error_correcting_code,#TestSVMClassical#,342

Before Change

        temp = [test_input[k] for k in sorted(test_input)]
        total_array = np.concatenate(temp)

        params = {
            "problem": {"name": "classification"},
            "algorithm": {
                "name": "SVM",
            },
            "multiclass_extension": {"name": "ErrorCorrectingCode", "code_size": 5},
        }

        algo_input = ClassificationInput(training_input, test_input, total_array)

        result = run_algorithm(params, algo_input)
        self.assertEqual(result["testing_accuracy"], 1.0)
        self.assertEqual(result["predicted_classes"],
                         ["A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "B",
                          "B", "B", "B", "B", "B", "B", "B", "B",

After Change

        temp = [test_input[k] for k in sorted(test_input)]
        total_array = np.concatenate(temp)

        result = SVM_Classical(training_input,
                               test_input,
                               total_array,
                               multiclass_extension=ErrorCorrectingCode(_RBF_SVC_Estimator,
                                                                        code_size=5)).run()

        self.assertEqual(result["testing_accuracy"], 1.0)
        self.assertEqual(result["predicted_classes"],
                         ["A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "B",

Instances