decision_tree_test.cpp File Reference

#include <mlpack/core.hpp>
#include <mlpack/core/util/mlpack_main.hpp>
#include <mlpack/methods/decision_tree/decision_tree_main.cpp>
#include "test_helper.hpp"
#include "../test_catch_tools.hpp"
#include "../catch.hpp"

Include dependency graph for decision_tree_test.cpp:

Classes
struct	DecisionTreeTestFixture

Macros
#define	BINDING_TYPE   BINDING_TYPE_TEST

Functions
void	ResetDTSettings ()
	TEST_CASE_METHOD (DecisionTreeTestFixture, "DecisionTreeOutputDimensionTest", "[DecisionTreeMainTest][BindingTests]")
	Check that number of output points and number of input points are equal.
	TEST_CASE_METHOD (DecisionTreeTestFixture, "DecisionTreeCategoricalOutputDimensionTest", "[DecisionTreeMainTest][BindingTests]")
	Check that number of output points and number of input points are equal for categorical dataset.
	TEST_CASE_METHOD (DecisionTreeTestFixture, "DecisionTreeMinimumLeafSizeTest", "[DecisionTreeMainTest][BindingTests]")
	Make sure minimum leaf size is always a non-negative number.
	TEST_CASE_METHOD (DecisionTreeTestFixture, "DecisionTreeNonNegativeMaximumDepthTest", "[DecisionTreeMainTest][BindingTests]")
	Make sure maximum depth is always a non-negative number.
	TEST_CASE_METHOD (DecisionTreeTestFixture, "DecisionMinimumGainSplitTest", "[DecisionTreeMainTest][BindingTests]")
	Make sure minimum gain split is always a fraction in range [0,1].
	TEST_CASE_METHOD (DecisionTreeTestFixture, "DecisionRegularisationTest", "[DecisionTreeMainTest][BindingTests]")
	Make sure minimum gain split produces regularised tree.
	TEST_CASE_METHOD (DecisionTreeTestFixture, "DecisionModelReuseTest", "[DecisionTreeMainTest][BindingTests]")
	Ensure that saved model can be used again.
	TEST_CASE_METHOD (DecisionTreeTestFixture, "DecisionTreeTrainingVerTest", "[DecisionTreeMainTest][BindingTests]")
	Make sure only one of training data or pre-trained model is passed.
	TEST_CASE_METHOD (DecisionTreeTestFixture, "DecisionModelCategoricalReuseTest", "[DecisionTreeMainTest][BindingTests]")
	Ensure that saved model trained on categorical dataset can be used again.
	TEST_CASE_METHOD (DecisionTreeTestFixture, "DecisionTreeMaximumDepthTest", "[DecisionTreeMainTest][BindingTests]")
	Check that different maximum depths give different results.

Detailed Description

Author

Manish Kumar

Test mlpackMain() of decision_tree_main.cpp.

mlpack is free software; you may redistribute it and/or modify it under the terms of the 3-clause BSD license. You should have received a copy of the 3-clause BSD license along with mlpack. If not, see http://www.opensource.org/licenses/BSD-3-Clause for more information.