package com.intel.daal.examples.decision_tree;
import com.intel.daal.algorithms.classifier.TreeNodeVisitor;
import com.intel.daal.algorithms.classifier.prediction.PredictionResult;
import com.intel.daal.algorithms.classifier.prediction.ModelInputId;
import com.intel.daal.algorithms.classifier.prediction.NumericTableInputId;
import com.intel.daal.algorithms.classifier.training.InputId;
import com.intel.daal.algorithms.classifier.training.TrainingResultId;
import com.intel.daal.algorithms.classifier.prediction.PredictionResultId;
import com.intel.daal.algorithms.decision_tree.classification.Model;
import com.intel.daal.algorithms.decision_tree.classification.prediction.*;
import com.intel.daal.algorithms.decision_tree.classification.training.*;
import com.intel.daal.algorithms.decision_tree.*;
import com.intel.daal.data_management.data.NumericTable;
import com.intel.daal.data_management.data.HomogenNumericTable;
import com.intel.daal.data_management.data.MergedNumericTable;
import com.intel.daal.data_management.data_source.DataSource;
import com.intel.daal.data_management.data_source.FileDataSource;
import com.intel.daal.examples.utils.Service;
import com.intel.daal.services.DaalContext;
import com.intel.daal.data_management.data.*;
class DtClsPrintNodeVisitor extends TreeNodeVisitor {
@Override
public boolean onLeafNode(long level, long response) {
if(level != 0)
printTab(level);
System.out.println("Level " + level + ", leaf node. Response value = " + response);
return true;
}
public boolean onSplitNode(long level, long featureIndex, double featureValue){
if(level != 0)
printTab(level);
System.out.println("Level " + level + ", split node. Feature index = " + featureIndex + ", feature value = " + featureValue);
return true;
}
private void printTab(long level) {
String s = "";
for (long i = 0; i < level; i++) {
s += " ";
}
System.out.print(s);
}
}
class DtClsTraverseModel {
private static final String trainDataset = "../data/batch/decision_tree_train.csv";
private static final String pruneDataset = "../data/batch/decision_tree_prune.csv";
private static final int nFeatures = 5;
private static final int nClasses = 5;
private static DaalContext context = new DaalContext();
public static void main(String[] args) throws java.io.FileNotFoundException, java.io.IOException {
TrainingResult trainingResult = trainModel();
printModel(trainingResult);
context.dispose();
}
private static TrainingResult trainModel() {
FileDataSource trainDataSource = new FileDataSource(context, trainDataset,
DataSource.DictionaryCreationFlag.DoDictionaryFromContext,
DataSource.NumericTableAllocationFlag.NotAllocateNumericTable);
NumericTable trainData = new HomogenNumericTable(context, Float.class, nFeatures, 0, NumericTable.AllocationFlag.NotAllocate);
NumericTable trainGroundTruth = new HomogenNumericTable(context, Float.class, 1, 0, NumericTable.AllocationFlag.NotAllocate);
MergedNumericTable mergedData = new MergedNumericTable(context);
mergedData.addNumericTable(trainData);
mergedData.addNumericTable(trainGroundTruth);
trainDataSource.loadDataBlock(mergedData);
FileDataSource pruneDataSource = new FileDataSource(context, pruneDataset,
DataSource.DictionaryCreationFlag.DoDictionaryFromContext,
DataSource.NumericTableAllocationFlag.NotAllocateNumericTable);
NumericTable pruneData = new HomogenNumericTable(context, Float.class, nFeatures, 0, NumericTable.AllocationFlag.NotAllocate);
NumericTable pruneGroundTruth = new HomogenNumericTable(context, Float.class, 1, 0, NumericTable.AllocationFlag.NotAllocate);
MergedNumericTable pruneMergedData = new MergedNumericTable(context);
pruneMergedData.addNumericTable(pruneData);
pruneMergedData.addNumericTable(pruneGroundTruth);
pruneDataSource.loadDataBlock(pruneMergedData);
TrainingBatch algorithm = new TrainingBatch(context, Float.class, TrainingMethod.defaultDense, nClasses);
algorithm.input.set(InputId.data, trainData);
algorithm.input.set(InputId.labels, trainGroundTruth);
algorithm.input.set(TrainingInputId.dataForPruning, pruneData);
algorithm.input.set(TrainingInputId.labelsForPruning, pruneGroundTruth);
return algorithm.compute();
}
private static void printModel(TrainingResult trainingResult) {
Model m = trainingResult.get(TrainingResultId.model);
DtClsPrintNodeVisitor visitor = new DtClsPrintNodeVisitor();
m.traverseDF(visitor);
}
}