2 // abstractdecisiontree.hpp
5 // Created by Abu Zaher Faridee on 7/22/12.
6 // Copyright (c) 2012 Schloss Lab. All rights reserved.
9 #ifndef RF_ABSTRACTDECISIONTREE_HPP
10 #define RF_ABSTRACTDECISIONTREE_HPP
12 #include "mothurout.h"
14 #include "rftreenode.hpp"
18 /**************************************************************************************************/
20 struct IntPairVectorSorter{
21 bool operator() (const pair<int, int>& firstPair, const pair<int, int>& secondPair) {
22 return firstPair.first < secondPair.first;
26 /**************************************************************************************************/
28 class AbstractDecisionTree{
32 AbstractDecisionTree(vector<vector<int> >& baseDataSet,
33 vector<int> globalDiscardedFeatureIndices,
34 OptimumFeatureSubsetSelector optimumFeatureSubsetSelector,
35 string treeSplitCriterion);
36 virtual ~AbstractDecisionTree(){}
41 virtual int createBootStrappedSamples();
42 virtual int getMinEntropyOfFeature(vector<int> featureVector, vector<int> outputVector, double& minEntropy, int& featureSplitValue, double& intrinsicValue);
43 virtual int getBestSplitAndMinEntropy(vector< pair<int, int> > featureOutputPairs, vector<int> splitPoints, double& minEntropy, int& minEntropyIndex, double& relatedIntrinsicValue);
44 virtual double calcIntrinsicValue(int numLessThanValueAtSplitPoint, int numGreaterThanValueAtSplitPoint, int numSamples);
45 virtual double calcSplitEntropy(vector< pair<int, int> > featureOutputPairs, int splitIndex, int numOutputClasses, bool);
47 virtual int getSplitPopulation(RFTreeNode* node, vector< vector<int> >& leftChildSamples, vector< vector<int> >& rightChildSamples);
48 virtual bool checkIfAlreadyClassified(RFTreeNode* treeNode, int& outputClass);
50 vector< vector<int> >& baseDataSet;
54 vector<int> outputClasses;
56 vector< vector<int> > bootstrappedTrainingSamples;
57 vector<int> bootstrappedTrainingSampleIndices;
58 vector< vector<int> > bootstrappedTestSamples;
59 vector<int> bootstrappedTestSampleIndices;
61 vector<vector<int> > testSampleFeatureVectors;
65 map<int, int> nodeMisclassificationCounts;
66 vector<int> globalDiscardedFeatureIndices;
67 int optimumFeatureSubsetSize;
68 string treeSplitCriterion;
75 /**************************************************************************************************/