moved FEAST Libraries

1 files changed, 166 insertions, 0 deletions

diff --git a/FEAST/FSToolbox/CondMI.c b/FEAST/FSToolbox/CondMI.c
new file mode 100644
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+++ b/FEAST/FSToolbox/CondMI.c
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+/*******************************************************************************
+** CondMI.c, implements the CMI criterion using a greedy forward search
+**
+** Initial Version - 19/08/2010
+** Updated - 23/06/2011
+**
+** Author - Adam Pocock
+** 
+** Part of the Feature Selection Toolbox, please reference
+** "Conditional Likelihood Maximisation: A Unifying Framework for Mutual
+** Information Feature Selection"
+** G. Brown, A. Pocock, M.-J. Zhao, M. Lujan
+** Journal of Machine Learning Research (JMLR), 2011
+**
+** Please check www.cs.manchester.ac.uk/~gbrown/fstoolbox for updates.
+** 
+** Copyright (c) 2010-2011, A. Pocock, G. Brown, The University of Manchester
+** All rights reserved.
+** 
+** Redistribution and use in source and binary forms, with or without modification,
+** are permitted provided that the following conditions are met:
+** 
+**   - Redistributions of source code must retain the above copyright notice, this 
+**     list of conditions and the following disclaimer.
+**   - Redistributions in binary form must reproduce the above copyright notice, 
+**     this list of conditions and the following disclaimer in the documentation 
+**     and/or other materials provided with the distribution.
+**   - Neither the name of The University of Manchester nor the names of its 
+**     contributors may be used to endorse or promote products derived from this 
+**     software without specific prior written permission.
+** 
+** THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+** ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 
+** WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 
+** DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
+** ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 
+** (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 
+** LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON 
+** ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 
+** (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 
+** SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+**
+*******************************************************************************/
+
+#include "FSAlgorithms.h"
+#include "FSToolbox.h"
+
+/* for memcpy */
+#include <string.h>
+
+/* MIToolbox includes */
+#include "MutualInformation.h"
+#include "ArrayOperations.h"
+
+double* CondMI(int k, int noOfSamples, int noOfFeatures, double *featureMatrix, double *classColumn, double *outputFeatures)
+{
+  /*holds the class MI values*/
+  double *classMI = (double *)CALLOC_FUNC(noOfFeatures,sizeof(double));
+  
+  char *selectedFeatures = (char *)CALLOC_FUNC(noOfFeatures,sizeof(char));
+  
+  /*holds the intra feature MI values*/
+  int sizeOfMatrix = k*noOfFeatures;
+  double *featureMIMatrix = (double *)CALLOC_FUNC(sizeOfMatrix,sizeof(double));
+  
+  double maxMI = 0.0;
+  int maxMICounter = -1;
+  
+  double **feature2D = (double**) CALLOC_FUNC(noOfFeatures,sizeof(double*));
+  
+  double score, currentScore, totalFeatureMI;
+  int currentHighestFeature;
+  
+  double *conditionVector = (double *) CALLOC_FUNC(noOfSamples,sizeof(double));
+  
+  int arrayPosition;
+  double mi, tripEntropy;
+  
+  int i,j,x;
+  
+  for(j = 0; j < noOfFeatures; j++)
+  {
+    feature2D[j] = featureMatrix + (int)j*noOfSamples;
+  }
+  
+  for (i = 0; i < sizeOfMatrix;i++)
+  {
+    featureMIMatrix[i] = -1;
+  }/*for featureMIMatrix - blank to -1*/
+
+  for (i = 0; i < noOfFeatures;i++)
+  {    
+    /*calculate mutual info
+    **double calculateMutualInformation(double *firstVector, double *secondVector, int vectorLength);
+    */
+    classMI[i] = calculateMutualInformation(feature2D[i], classColumn, noOfSamples);
+    
+    if (classMI[i] > maxMI)
+    {
+      maxMI = classMI[i];
+      maxMICounter = i;
+    }/*if bigger than current maximum*/
+  }/*for noOfFeatures - filling classMI*/
+  
+  selectedFeatures[maxMICounter] = 1;
+  outputFeatures[0] = maxMICounter;
+  
+  memcpy(conditionVector,feature2D[maxMICounter],sizeof(double)*noOfSamples);
+      
+  /*****************************************************************************
+  ** We have populated the classMI array, and selected the highest
+  ** MI feature as the first output feature
+  ** Now we move into the CondMI algorithm
+  *****************************************************************************/
+  
+  for (i = 1; i < k; i++)
+  {
+    score = 0.0;
+    currentHighestFeature = -1;
+    currentScore = 0.0;
+    totalFeatureMI = 0.0;
+    
+    for (j = 0; j < noOfFeatures; j++)
+    {
+      /*if we haven't selected j*/
+      if (selectedFeatures[j] == 0)
+      {
+        currentScore = 0.0;
+        totalFeatureMI = 0.0;
+        
+        /*double calculateConditionalMutualInformation(double *firstVector, double *targetVector, double *conditionVector, int vectorLength);*/
+        currentScore = calculateConditionalMutualInformation(feature2D[j],classColumn,conditionVector,noOfSamples);
+        
+			  if (currentScore > score)
+			  {
+				  score = currentScore;
+				  currentHighestFeature = j;
+			  }
+			}/*if j is unselected*/
+	  }/*for number of features*/
+  
+    outputFeatures[i] = currentHighestFeature;
+    
+    if (currentHighestFeature != -1)
+    {
+      selectedFeatures[currentHighestFeature] = 1;
+      mergeArrays(feature2D[currentHighestFeature],conditionVector,conditionVector,noOfSamples);
+    }
+  
+  }/*for the number of features to select*/
+  
+  FREE_FUNC(classMI);
+  FREE_FUNC(conditionVector);
+  FREE_FUNC(feature2D);
+  FREE_FUNC(featureMIMatrix);
+  FREE_FUNC(selectedFeatures);
+  
+  classMI = NULL;
+  conditionVector = NULL;
+  feature2D = NULL;
+  featureMIMatrix = NULL;
+  selectedFeatures = NULL;
+  
+  return outputFeatures;
+}/*CondMI(int,int,int,double[][],double[],double[])*/
+