Member DirectGraphicalModels::CGraphPairwise::removeEdge (size_t edge): Optimize the edge removement
Member DirectGraphicalModels::CGraphWeiss::vec_pEdge_t: Use smart pointers here
Member DirectGraphicalModels::CGraphWeiss::vec_pNode_t: Use smart pointers here
Class DirectGraphicalModels::CInferTree: Check the application of this class to DAGs and mixed graphs
Member DirectGraphicalModels::CPriorTriplet::calculatePrior (void) const: Implement this function
Member DirectGraphicalModels::CTrainEdgeConcat< Trainer, Concatenator >::calculateEdgePotentials (const Mat &featureVector1, const Mat &featureVector2, const vec_float_t &vParams) const: : Incorporate the node potential weight into the model parameters
Member DirectGraphicalModels::CTrainNodeMsRF::reset (void): Check! It may be very slow here
Member DirectGraphicalModels::CTrainTriplet::loadFile (FILE *pFile): Implement load() function
Member DirectGraphicalModels::CTrainTriplet::saveFile (FILE *pFile) const: Implement save() function
Member DirectGraphicalModels::parallel::shuffleRows (Mat &m): Eliminate the bias, caused by parallel processing.