bool RandomForests::combineModels( const RandomForests &forest ){
if( !getTrained() ){
errorLog << "combineModels( const RandomForests &forest ) - This instance has not been trained!" << endl;
return false;
}
if( !forest.getTrained() ){
errorLog << "combineModels( const RandomForests &forest ) - This external forest instance has not been trained!" << endl;
return false;
}
if( this->getNumInputDimensions() != forest.getNumInputDimensions() ) {
errorLog << "combineModels( const RandomForests &forest ) - The number of input dimensions of the external forest (";
errorLog << forest.getNumInputDimensions() << ") does not match the number of input dimensions of this instance (";
errorLog << this->getNumInputDimensions() << ")!" << endl;
return false;
}
//Add the trees in the other forest to this model
DecisionTreeNode *node;
for(UINT i=0; i<forest.getForestSize(); i++){
node = forest.getTree(i);
if( node ){
this->forest.push_back( node->deepCopy() );
forestSize++;
}
}
return true;
}
bool MLBase::getModelTrained() const{ return getTrained(); }
