numDecisionTrees(numDecisionTrees),
numSamples((int)dataSet.size()),
numFeatures((int)(dataSet[0].size() - 1)),
-globalDiscardedFeatureIndices(getGlobalDiscardedFeatureIndices()),
globalVariableImportanceList(numFeatures, 0),
treeSplitCriterion(treeSplitCriterion) {
m = MothurOut::getInstance();
+ globalDiscardedFeatureIndices = getGlobalDiscardedFeatureIndices();
// TODO: double check if the implemenatation of 'globalOutOfBagEstimates' is correct
}
vector<int> Forest::getGlobalDiscardedFeatureIndices() {
try {
- vector<int> globalDiscardedFeatureIndices;
+ //vector<int> globalDiscardedFeatureIndices;
+ //globalDiscardedFeatureIndices.push_back(1);
// calculate feature vectors
- vector< vector<int> > featureVectors(numFeatures, vector<int>(numSamples, 0));
+ vector< vector<int> > featureVectors(numFeatures, vector<int>(numSamples, 0) );
for (int i = 0; i < numSamples; i++) {
if (m->control_pressed) { return globalDiscardedFeatureIndices; }
for (int j = 0; j < numFeatures; j++) { featureVectors[j][i] = dataSet[i][j]; }