Ejemplo n.º 1
0
// static
void GResamplingAdaBoost::test()
{
	GDecisionTree* pLearner = new GDecisionTree();
	pLearner->useRandomDivisions();
	GResamplingAdaBoost boost(pLearner, true, new GLearnerLoader());
	boost.basicTest(0.753, 0.92);
}
Ejemplo n.º 2
0
// static
void GBayesianModelCombination::test()
{
	GBayesianModelCombination bmc;
	for(size_t i = 0; i < 32; i++)
	{
		GDecisionTree* pTree = new GDecisionTree();
		pTree->useRandomDivisions();
		bmc.addLearner(pTree);
	}
	bmc.basicTest(0.76, 0.928, 0.01);
}
Ejemplo n.º 3
0
// static
void GBayesianModelAveraging::test()
{
	GBayesianModelAveraging bma;
	for(size_t i = 0; i < 32; i++)
	{
		GDecisionTree* pTree = new GDecisionTree();
		pTree->useRandomDivisions();
		bma.addLearner(pTree);
	}
	bma.basicTest(0.708, 0.816, 0.01);
}
Ejemplo n.º 4
0
// static
void GBomb::test()
{
	GBomb bomb;
	for(size_t i = 0; i < 32; i++)
	{
		GDecisionTree* pTree = new GDecisionTree();
		pTree->useRandomDivisions();
		bomb.addLearner(pTree);
	}
	bomb.basicTest(0.76, 0.765, 0.01);
}
Ejemplo n.º 5
0
// static
void GBag::test()
{
	GBag bag;
	for(size_t i = 0; i < 64; i++)
	{
		GDecisionTree* pTree = new GDecisionTree();
		pTree->useRandomDivisions();
		bag.addLearner(pTree);
	}
	bag.basicTest(0.764, 0.93, 0.01);
}
Ejemplo n.º 6
0
// static
void GBag::test()
{
	GRand rand(0);
	GBag bag(rand);
	for(size_t i = 0; i < 64; i++)
	{
		GDecisionTree* pTree = new GDecisionTree(rand);
		pTree->useRandomDivisions();
		bag.addLearner(pTree);
	}
	bag.basicTest(0.767, 0.8, 0.01);
}