added classify.shared command and random forest files. added count file to pcr.seqs...

[mothur.git] / abstractdecisiontree.hpp

diff --git a/abstractdecisiontree.hpp b/abstractdecisiontree.hpp
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+++ b/abstractdecisiontree.hpp
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+//
+//  abstractdecisiontree.hpp
+//  rrf-fs-prototype
+//
+//  Created by Abu Zaher Faridee on 7/22/12.
+//  Copyright (c) 2012 Schloss Lab. All rights reserved.
+//
+
+#ifndef rrf_fs_prototype_abstractdecisiontree_hpp
+#define rrf_fs_prototype_abstractdecisiontree_hpp
+
+#include "mothurout.h"
+#include "macros.h"
+#include "rftreenode.hpp"
+
+#define DEBUG_MODE
+
+/**************************************************************************************************/
+
+class AbstractDecisionTree{
+  
+public:
+  
+    AbstractDecisionTree(vector<vector<int> >baseDataSet, 
+                       vector<int> globalDiscardedFeatureIndices, 
+                       OptimumFeatureSubsetSelector optimumFeatureSubsetSelector, 
+                       string treeSplitCriterion);    
+    virtual ~AbstractDecisionTree(){}
+    
+  
+protected:
+  
+    virtual int createBootStrappedSamples();
+    virtual int getMinEntropyOfFeature(vector<int> featureVector, vector<int> outputVector, double& minEntropy, int& featureSplitValue, double& intrinsicValue);
+    virtual int getBestSplitAndMinEntropy(vector< vector<int> > featureOutputPairs, vector<int> splitPoints, double& minEntropy, int& minEntropyIndex, double& relatedIntrinsicValue);
+    virtual double calcIntrinsicValue(int numLessThanValueAtSplitPoint, int numGreaterThanValueAtSplitPoint, int numSamples);
+    virtual double calcSplitEntropy(vector< vector<int> > featureOutputPairs, int splitIndex, int numOutputClasses, bool);
+    virtual int getSplitPopulation(RFTreeNode* node, vector< vector<int> >& leftChildSamples, vector< vector<int> >& rightChildSamples);
+    virtual bool checkIfAlreadyClassified(RFTreeNode* treeNode, int& outputClass);
+
+    vector< vector<int> > baseDataSet;
+    int numSamples;
+    int numFeatures;
+    int numOutputClasses;
+    vector<int> outputClasses;
+    vector< vector<int> > bootstrappedTrainingSamples;
+    vector<int> bootstrappedTrainingSampleIndices;
+    vector< vector<int> > bootstrappedTestSamples;
+    vector<int> bootstrappedTestSampleIndices;
+    
+    RFTreeNode* rootNode;
+    vector<int> globalDiscardedFeatureIndices;
+    int optimumFeatureSubsetSize;
+    string treeSplitCriterion;
+    MothurOut* m;
+  
+private:
+    
+  
+};
+/**************************************************************************************************/
+
+#endif