#include "daal.h"
#include "service.h"
using namespace std;
using namespace daal;
using namespace daal::algorithms::decision_forest::regression;
const string trainDatasetFileName = "../data/batch/df_regression_train.csv";
const size_t categoricalFeaturesIndices[] = { 3 };
const size_t nFeatures = 13;
const size_t nTrees = 2;
training::ResultPtr trainModel();
void loadData(const std::string& fileName, NumericTablePtr& pData, NumericTablePtr& pDependentVar);
void printModel(const daal::algorithms::decision_forest::regression::Model& m);
int main(int argc, char *argv[])
{
checkArguments(argc, argv, 1, &trainDatasetFileName);
training::ResultPtr trainingResult = trainModel();
printModel(*trainingResult->get(training::model));
return 0;
}
training::ResultPtr trainModel()
{
NumericTablePtr trainData;
NumericTablePtr trainDependentVariable;
loadData(trainDatasetFileName, trainData, trainDependentVariable);
training::Batch<> algorithm;
algorithm.input.set(training::data, trainData);
algorithm.input.set(training::dependentVariable, trainDependentVariable);
algorithm.parameter.nTrees = nTrees;
algorithm.compute();
return algorithm.getResult();
}
void loadData(const std::string& fileName, NumericTablePtr& pData, NumericTablePtr& pDependentVar)
{
FileDataSource<CSVFeatureManager> trainDataSource(fileName,
DataSource::notAllocateNumericTable,
DataSource::doDictionaryFromContext);
pData.reset(new HomogenNumericTable<>(nFeatures, 0, NumericTable::notAllocate));
pDependentVar.reset(new HomogenNumericTable<>(1, 0, NumericTable::notAllocate));
NumericTablePtr mergedData(new MergedNumericTable(pData, pDependentVar));
trainDataSource.loadDataBlock(mergedData.get());
NumericTableDictionaryPtr pDictionary = pData->getDictionarySharedPtr();
for(size_t i = 0, n = sizeof(categoricalFeaturesIndices) / sizeof(categoricalFeaturesIndices[0]); i < n; ++i)
(*pDictionary)[categoricalFeaturesIndices[i]].featureType = data_feature_utils::DAAL_CATEGORICAL;
}
class PrintNodeVisitor : public daal::algorithms::tree_utils::regression::TreeNodeVisitor
{
public:
virtual bool onLeafNode(const daal::algorithms::tree_utils::regression::LeafNodeDescriptor &desc)
{
for(size_t i = 0; i < desc.level; ++i)
std::cout << " ";
std::cout << "Level " << desc.level << ", leaf node. Response value = " << desc.response << ", Impurity = " << desc.impurity <<
", Number of samples = " << desc.nNodeSampleCount << std::endl;
return true;
}
virtual bool onSplitNode(const daal::algorithms::tree_utils::regression::SplitNodeDescriptor &desc)
{
for(size_t i = 0; i < desc.level; ++i)
std::cout << " ";
std::cout << "Level " << desc.level << ", split node. Feature index = " << desc.featureIndex <<
", feature value = " << desc.featureValue << ", Impurity = " << desc.impurity <<
", Number of samples = " << desc.nNodeSampleCount << std::endl;
return true;
}
};
void printModel(const daal::algorithms::decision_forest::regression::Model& m)
{
PrintNodeVisitor visitor;
std::cout << "Number of trees: " << m.getNumberOfTrees() << std::endl;
for(size_t i = 0, n = m.getNumberOfTrees(); i < n; ++i)
{
std::cout << "Tree #" << i << std::endl;
m.traverseDFS(i, visitor);
}
}