/*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
/*
* Distribution.java
* Copyright (C) 1999-2012 University of Waikato, Hamilton, New Zealand
*
*/
package weka.classifiers.trees.j48;
import java.io.Serializable;
import java.util.Enumeration;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.RevisionHandler;
import weka.core.RevisionUtils;
import weka.core.Utils;
/**
* Class for handling a distribution of class values.
*
* @author Eibe Frank (eibe@cs.waikato.ac.nz)
* @version $Revision: 8034 $
*/
public class Distribution
implements Cloneable, Serializable, RevisionHandler {
/** for serialization */
private static final long serialVersionUID = 8526859638230806576L;
/** Weight of instances per class per bag. */
private double m_perClassPerBag[][];
/** Weight of instances per bag. */
private double m_perBag[];
/** Weight of instances per class. */
private double m_perClass[];
/** Total weight of instances. */
private double totaL;
/**
* Creates and initializes a new distribution.
*/
public Distribution(int numBags,int numClasses) {
int i;
m_perClassPerBag = new double [numBags][0];
m_perBag = new double [numBags];
m_perClass = new double [numClasses];
for (i=0;i<numBags;i++)
m_perClassPerBag[i] = new double [numClasses];
totaL = 0;
}
/**
* Creates and initializes a new distribution using the given
* array. WARNING: it just copies a reference to this array.
*/
public Distribution(double [][] table) {
int i, j;
m_perClassPerBag = table;
m_perBag = new double [table.length];
m_perClass = new double [table[0].length];
for (i = 0; i < table.length; i++)
for (j = 0; j < table[i].length; j++) {
m_perBag[i] += table[i][j];
m_perClass[j] += table[i][j];
totaL += table[i][j];
}
}
/**
* Creates a distribution with only one bag according
* to instances in source.
*
* @exception Exception if something goes wrong
*/
public Distribution(Instances source) throws Exception {
m_perClassPerBag = new double [1][0];
m_perBag = new double [1];
totaL = 0;
m_perClass = new double [source.numClasses()];
m_perClassPerBag[0] = new double [source.numClasses()];
Enumeration enu = source.enumerateInstances();
while (enu.hasMoreElements())
add(0,(Instance) enu.nextElement());
}
/**
* Creates a distribution according to given instances and
* split model.
*
* @exception Exception if something goes wrong
*/
public Distribution(Instances source,
ClassifierSplitModel modelToUse)
throws Exception {
int index;
Instance instance;
double[] weights;
m_perClassPerBag = new double [modelToUse.numSubsets()][0];
m_perBag = new double [modelToUse.numSubsets()];
totaL = 0;
m_perClass = new double [source.numClasses()];
for (int i = 0; i < modelToUse.numSubsets(); i++)
m_perClassPerBag[i] = new double [source.numClasses()];
Enumeration enu = source.enumerateInstances();
while (enu.hasMoreElements()) {
instance = (Instance) enu.nextElement();
index = modelToUse.whichSubset(instance);
if (index != -1)
add(index, instance);
else {
weights = modelToUse.weights(instance);
addWeights(instance, weights);
}
}
}
/**
* Creates distribution with only one bag by merging all
* bags of given distribution.
*/
public Distribution(Distribution toMerge) {
totaL = toMerge.totaL;
m_perClass = new double [toMerge.numClasses()];
System.arraycopy(toMerge.m_perClass,0,m_perClass,0,toMerge.numClasses());
m_perClassPerBag = new double [1] [0];
m_perClassPerBag[0] = new double [toMerge.numClasses()];
System.arraycopy(toMerge.m_perClass,0,m_perClassPerBag[0],0,
toMerge.numClasses());
m_perBag = new double [1];
m_perBag[0] = totaL;
}
/**
* Creates distribution with two bags by merging all bags apart of
* the indicated one.
*/
public Distribution(Distribution toMerge, int index) {
int i;
totaL = toMerge.totaL;
m_perClass = new double [toMerge.numClasses()];
System.arraycopy(toMerge.m_perClass,0,m_perClass,0,toMerge.numClasses());
m_perClassPerBag = new double [2] [0];
m_perClassPerBag[0] = new double [toMerge.numClasses()];
System.arraycopy(toMerge.m_perClassPerBag[index],0,m_perClassPerBag[0],0,
toMerge.numClasses());
m_perClassPerBag[1] = new double [toMerge.numClasses()];
for (i=0;i<toMerge.numClasses();i++)
m_perClassPerBag[1][i] = toMerge.m_perClass[i]-m_perClassPerBag[0][i];
m_perBag = new double [2];
m_perBag[0] = toMerge.m_perBag[index];
m_perBag[1] = totaL-m_perBag[0];
}
/**
* Returns number of non-empty bags of distribution.
*/
public final int actualNumBags() {
int returnValue = 0;
int i;
for (i=0;i<m_perBag.length;i++)
if (Utils.gr(m_perBag[i],0))
returnValue++;
return returnValue;
}
/**
* Returns number of classes actually occuring in distribution.
*/
public final int actualNumClasses() {
int returnValue = 0;
int i;
for (i=0;i<m_perClass.length;i++)
if (Utils.gr(m_perClass[i],0))
returnValue++;
return returnValue;
}
/**
* Returns number of classes actually occuring in given bag.
*/
public final int actualNumClasses(int bagIndex) {
int returnValue = 0;
int i;
for (i=0;i<m_perClass.length;i++)
if (Utils.gr(m_perClassPerBag[bagIndex][i],0))
returnValue++;
return returnValue;
}
/**
* Adds given instance to given bag.
*
* @exception Exception if something goes wrong
*/
public final void add(int bagIndex,Instance instance)
throws Exception {
int classIndex;
double weight;
classIndex = (int)instance.classValue();
weight = instance.weight();
m_perClassPerBag[bagIndex][classIndex] =
m_perClassPerBag[bagIndex][classIndex]+weight;
m_perBag[bagIndex] = m_perBag[bagIndex]+weight;
m_perClass[classIndex] = m_perClass[classIndex]+weight;
totaL = totaL+weight;
}
/**
* Subtracts given instance from given bag.
*
* @exception Exception if something goes wrong
*/
public final void sub(int bagIndex,Instance instance)
throws Exception {
int classIndex;
double weight;
classIndex = (int)instance.classValue();
weight = instance.weight();
m_perClassPerBag[bagIndex][classIndex] =
m_perClassPerBag[bagIndex][classIndex]-weight;
m_perBag[bagIndex] = m_perBag[bagIndex]-weight;
m_perClass[classIndex] = m_perClass[classIndex]-weight;
totaL = totaL-weight;
}
/**
* Adds counts to given bag.
*/
public final void add(int bagIndex, double[] counts) {
double sum = Utils.sum(counts);
for (int i = 0; i < counts.length; i++)
m_perClassPerBag[bagIndex][i] += counts[i];
m_perBag[bagIndex] = m_perBag[bagIndex]+sum;
for (int i = 0; i < counts.length; i++)
m_perClass[i] = m_perClass[i]+counts[i];
totaL = totaL+sum;
}
/**
* Adds all instances with unknown values for given attribute, weighted
* according to frequency of instances in each bag.
*
* @exception Exception if something goes wrong
*/
public final void addInstWithUnknown(Instances source,
int attIndex)
throws Exception {
double [] probs;
double weight,newWeight;
int classIndex;
Instance instance;
int j;
probs = new double [m_perBag.length];
for (j=0;j<m_perBag.length;j++) {
if (Utils.eq(totaL, 0)) {
probs[j] = 1.0 / probs.length;
} else {
probs[j] = m_perBag[j]/totaL;
}
}
Enumeration enu = source.enumerateInstances();
while (enu.hasMoreElements()) {
instance = (Instance) enu.nextElement();
if (instance.isMissing(attIndex)) {
classIndex = (int)instance.classValue();
weight = instance.weight();
m_perClass[classIndex] = m_perClass[classIndex]+weight;
totaL = totaL+weight;
for (j = 0; j < m_perBag.length; j++) {
newWeight = probs[j]*weight;
m_perClassPerBag[j][classIndex] = m_perClassPerBag[j][classIndex]+
newWeight;
m_perBag[j] = m_perBag[j]+newWeight;
}
}
}
}
/**
* Adds all instances in given range to given bag.
*
* @exception Exception if something goes wrong
*/
public final void addRange(int bagIndex,Instances source,
int startIndex, int lastPlusOne)
throws Exception {
double sumOfWeights = 0;
int classIndex;
Instance instance;
int i;
for (i = startIndex; i < lastPlusOne; i++) {
instance = (Instance) source.instance(i);
classIndex = (int)instance.classValue();
sumOfWeights = sumOfWeights+instance.weight();
m_perClassPerBag[bagIndex][classIndex] += instance.weight();
m_perClass[classIndex] += instance.weight();
}
m_perBag[bagIndex] += sumOfWeights;
totaL += sumOfWeights;
}
/**
* Adds given instance to all bags weighting it according to given weights.
*
* @exception Exception if something goes wrong
*/
public final void addWeights(Instance instance,
double [] weights)
throws Exception {
int classIndex;
int i;
classIndex = (int)instance.classValue();
for (i=0;i<m_perBag.length;i++) {
double weight = instance.weight() * weights[i];
m_perClassPerBag[i][classIndex] = m_perClassPerBag[i][classIndex] + weight;
m_perBag[i] = m_perBag[i] + weight;
m_perClass[classIndex] = m_perClass[classIndex] + weight;
totaL = totaL + weight;
}
}
/**
* Checks if at least two bags contain a minimum number of instances.
*/
public final boolean check(double minNoObj) {
int counter = 0;
int i;
for (i=0;i<m_perBag.length;i++)
if (Utils.grOrEq(m_perBag[i],minNoObj))
counter++;
if (counter > 1)
return true;
else
return false;
}
/**
* Clones distribution (Deep copy of distribution).
*/
public final Object clone() {
int i,j;
Distribution newDistribution = new Distribution (m_perBag.length,
m_perClass.length);
for (i=0;i<m_perBag.length;i++) {
newDistribution.m_perBag[i] = m_perBag[i];
for (j=0;j<m_perClass.length;j++)
newDistribution.m_perClassPerBag[i][j] = m_perClassPerBag[i][j];
}
for (j=0;j<m_perClass.length;j++)
newDistribution.m_perClass[j] = m_perClass[j];
newDistribution.totaL = totaL;
return newDistribution;
}
/**
* Deletes given instance from given bag.
*
* @exception Exception if something goes wrong
*/
public final void del(int bagIndex,Instance instance)
throws Exception {
int classIndex;
double weight;
classIndex = (int)instance.classValue();
weight = instance.weight();
m_perClassPerBag[bagIndex][classIndex] =
m_perClassPerBag[bagIndex][classIndex]-weight;
m_perBag[bagIndex] = m_perBag[bagIndex]-weight;
m_perClass[classIndex] = m_perClass[classIndex]-weight;
totaL = totaL-weight;
}
/**
* Deletes all instances in given range from given bag.
*
* @exception Exception if something goes wrong
*/
public final void delRange(int bagIndex,Instances source,
int startIndex, int lastPlusOne)
throws Exception {
double sumOfWeights = 0;
int classIndex;
Instance instance;
int i;
for (i = startIndex; i < lastPlusOne; i++) {
instance = (Instance) source.instance(i);
classIndex = (int)instance.classValue();
sumOfWeights = sumOfWeights+instance.weight();
m_perClassPerBag[bagIndex][classIndex] -= instance.weight();
m_perClass[classIndex] -= instance.weight();
}
m_perBag[bagIndex] -= sumOfWeights;
totaL -= sumOfWeights;
}
/**
* Prints distribution.
*/
public final String dumpDistribution() {
StringBuffer text;
int i,j;
text = new StringBuffer();
for (i=0;i<m_perBag.length;i++) {
text.append("Bag num "+i+"\n");
for (j=0;j<m_perClass.length;j++)
text.append("Class num "+j+" "+m_perClassPerBag[i][j]+"\n");
}
return text.toString();
}
/**
* Sets all counts to zero.
*/
public final void initialize() {
for (int i = 0; i < m_perClass.length; i++)
m_perClass[i] = 0;
for (int i = 0; i < m_perBag.length; i++)
m_perBag[i] = 0;
for (int i = 0; i < m_perBag.length; i++)
for (int j = 0; j < m_perClass.length; j++)
m_perClassPerBag[i][j] = 0;
totaL = 0;
}
/**
* Returns matrix with distribution of class values.
*/
public final double[][] matrix() {
return m_perClassPerBag;
}
/**
* Returns index of bag containing maximum number of instances.
*/
public final int maxBag() {
double max;
int maxIndex;
int i;
max = 0;
maxIndex = -1;
for (i=0;i<m_perBag.length;i++)
if (Utils.grOrEq(m_perBag[i],max)) {
max = m_perBag[i];
maxIndex = i;
}
return maxIndex;
}
/**
* Returns class with highest frequency over all bags.
*/
public final int maxClass() {
double maxCount = 0;
int maxIndex = 0;
int i;
for (i=0;i<m_perClass.length;i++)
if (Utils.gr(m_perClass[i],maxCount)) {
maxCount = m_perClass[i];
maxIndex = i;
}
return maxIndex;
}
/**
* Returns class with highest frequency for given bag.
*/
public final int maxClass(int index) {
double maxCount = 0;
int maxIndex = 0;
int i;
if (Utils.gr(m_perBag[index],0)) {
for (i=0;i<m_perClass.length;i++)
if (Utils.gr(m_perClassPerBag[index][i],maxCount)) {
maxCount = m_perClassPerBag[index][i];
maxIndex = i;
}
return maxIndex;
}else
return maxClass();
}
/**
* Returns number of bags.
*/
public final int numBags() {
return m_perBag.length;
}
/**
* Returns number of classes.
*/
public final int numClasses() {
return m_perClass.length;
}
/**
* Returns perClass(maxClass()).
*/
public final double numCorrect() {
return m_perClass[maxClass()];
}
/**
* Returns perClassPerBag(index,maxClass(index)).
*/
public final double numCorrect(int index) {
return m_perClassPerBag[index][maxClass(index)];
}
/**
* Returns total-numCorrect().
*/
public final double numIncorrect() {
return totaL-numCorrect();
}
/**
* Returns perBag(index)-numCorrect(index).
*/
public final double numIncorrect(int index) {
return m_perBag[index]-numCorrect(index);
}
/**
* Returns number of (possibly fractional) instances of given class in
* given bag.
*/
public final double perClassPerBag(int bagIndex, int classIndex) {
return m_perClassPerBag[bagIndex][classIndex];
}
/**
* Returns number of (possibly fractional) instances in given bag.
*/
public final double perBag(int bagIndex) {
return m_perBag[bagIndex];
}
/**
* Returns number of (possibly fractional) instances of given class.
*/
public final double perClass(int classIndex) {
return m_perClass[classIndex];
}
/**
* Returns relative frequency of class over all bags with
* Laplace correction.
*/
public final double laplaceProb(int classIndex) {
return (m_perClass[classIndex] + 1) /
(totaL + (double) m_perClass.length);
}
/**
* Returns relative frequency of class for given bag.
*/
public final double laplaceProb(int classIndex, int intIndex) {
if (Utils.gr(m_perBag[intIndex],0))
return (m_perClassPerBag[intIndex][classIndex] + 1.0) /
(m_perBag[intIndex] + (double) m_perClass.length);
else
return laplaceProb(classIndex);
}
/**
* Returns relative frequency of class over all bags.
*/
public final double prob(int classIndex) {
if (!Utils.eq(totaL, 0)) {
return m_perClass[classIndex]/totaL;
} else {
return 0;
}
}
/**
* Returns relative frequency of class for given bag.
*/
public final double prob(int classIndex,int intIndex) {
if (Utils.gr(m_perBag[intIndex],0))
return m_perClassPerBag[intIndex][classIndex]/m_perBag[intIndex];
else
return prob(classIndex);
}
/**
* Subtracts the given distribution from this one. The results
* has only one bag.
*/
public final Distribution subtract(Distribution toSubstract) {
Distribution newDist = new Distribution(1,m_perClass.length);
newDist.m_perBag[0] = totaL-toSubstract.totaL;
newDist.totaL = newDist.m_perBag[0];
for (int i = 0; i < m_perClass.length; i++) {
newDist.m_perClassPerBag[0][i] = m_perClass[i] - toSubstract.m_perClass[i];
newDist.m_perClass[i] = newDist.m_perClassPerBag[0][i];
}
return newDist;
}
/**
* Returns total number of (possibly fractional) instances.
*/
public final double total() {
return totaL;
}
/**
* Shifts given instance from one bag to another one.
*
* @exception Exception if something goes wrong
*/
public final void shift(int from,int to,Instance instance)
throws Exception {
int classIndex;
double weight;
classIndex = (int)instance.classValue();
weight = instance.weight();
m_perClassPerBag[from][classIndex] -= weight;
m_perClassPerBag[to][classIndex] += weight;
m_perBag[from] -= weight;
m_perBag[to] += weight;
}
/**
* Shifts all instances in given range from one bag to another one.
*
* @exception Exception if something goes wrong
*/
public final void shiftRange(int from,int to,Instances source,
int startIndex,int lastPlusOne)
throws Exception {
int classIndex;
double weight;
Instance instance;
int i;
for (i = startIndex; i < lastPlusOne; i++) {
instance = (Instance) source.instance(i);
classIndex = (int)instance.classValue();
weight = instance.weight();
m_perClassPerBag[from][classIndex] -= weight;
m_perClassPerBag[to][classIndex] += weight;
m_perBag[from] -= weight;
m_perBag[to] += weight;
}
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 8034 $");
}
}