CPT1(const DatasetMetadata* metadata, int self, const vector<int>& parents) : CPT(self, parents) {
Feature* selfFeature = metadata->featureList[self];
Feature* parentFeature = metadata->classVariable;
table.resize(selfFeature->getRange());
for (int i = 0; i < table.size(); ++i)
table[i].resize(parentFeature->getRange());
}
double BayesNet::computeMutualInfo(int featureIdxI, int featureIdxJ) const {
Feature* Y = metadata->classVariable;
Feature* Xi = metadata->featureList[featureIdxI];
Feature* Xj = metadata->featureList[featureIdxJ];
int rangeY = Y->getRange();
int rangeXi = Xi->getRange();
int rangeXj = Xj->getRange();
vector<int> YOccurance;
YOccurance.resize(rangeY);
vector<vector<int> > YXiOccurance;
YXiOccurance.resize(rangeY);
for (int valY = 0; valY < rangeY; ++valY)
YXiOccurance[valY].resize(rangeXi);
vector<vector<int> > YXjOccurance;
YXjOccurance.resize(rangeY);
for (int valY = 0; valY < rangeY; ++valY)
YXjOccurance[valY].resize(rangeXj);
vector<vector<vector<int> > > YXiXjOccurance;
YXiXjOccurance.resize(rangeY);
for (int valY = 0; valY < rangeY; ++valY) {
YXiXjOccurance[valY].resize(rangeXi);
for (int valXi = 0; valXi < rangeXi; ++valXi)
YXiXjOccurance[valY][valXi].resize(rangeXj);
}
for (int i = 0; i < instances.size(); ++i) {
Instance* inst = instances[i];
int valY = (int)round(inst->classLabel);
int valXi = (int)round(inst->featureVector[featureIdxI]);
int valXj = (int)round(inst->featureVector[featureIdxJ]);
YOccurance[valY]++;
YXiOccurance[valY][valXi]++;
YXjOccurance[valY][valXj]++;
YXiXjOccurance[valY][valXi][valXj]++;
}
int total = (int)instances.size();
double mutualInfo = 0.0;
for (int valY = 0; valY < rangeY; ++valY) {
for (int valXi = 0; valXi < rangeXi; ++valXi) {
for (int valXj = 0; valXj < rangeXj; ++valXj) {
double pXiXjY = (YXiXjOccurance[valY][valXi][valXj] + 1.0) /
(total + rangeXi * rangeXj * rangeY);
double pXiXj_Y = (YXiXjOccurance[valY][valXi][valXj] + 1.0) /
(YOccurance[valY] + rangeXi * rangeXj);
double pXi_Y = (YXiOccurance[valY][valXi] + 1.0) /
(YOccurance[valY] + rangeXi);
double pXj_Y = (YXjOccurance[valY][valXj] + 1.0) /
(YOccurance[valY] + rangeXj);
mutualInfo += pXiXjY * log2(pXiXj_Y / (pXi_Y * pXj_Y));
}
}
}
return mutualInfo;
}
CPT2(const DatasetMetadata* metadata, int self, const vector<int>& parents) : CPT(self, parents) {
Feature* selfFeature = metadata->featureList[self];
Feature* parentFeature0 = metadata->featureList[parents[0]];
Feature* parentFeature1 = metadata->classVariable;
table.resize(selfFeature->getRange());
for (int i = 0; i < table.size(); ++i) {
table[i].resize(parentFeature0->getRange());
for (int j = 0; j < table[i].size(); ++j)
table[i][j].resize(parentFeature1->getRange());
}
}
CPT0(const DatasetMetadata* metadata, int self, const vector<int>& parents) : CPT(self, parents) {
Feature* selfFeature = metadata->classVariable;
table.resize(selfFeature->getRange());
}
