void opf_OPFAgglomerativeLearning(Subgraph **sgtrain, Subgraph **sgeval){ int n, i = 1; float Acc; /*while there exists misclassified samples in sgeval*/ do{ fflush(stdout); fprintf(stdout, "\nrunning iteration ... %d ", i++); n = 0; opf_OPFTraining(*sgtrain); opf_OPFClassifying(*sgtrain, *sgeval); Acc = opf_Accuracy(*sgeval); fprintf(stdout," %f",Acc*100); opf_MoveMisclassifiedNodes(&(*sgeval), &(*sgtrain), &n); fprintf(stdout,"\nMisclassified nodes: %d",n); }while(n); }
//Learning function: it executes the learning procedure for CompGraph replacing the //missclassified samples in the evaluation set by non prototypes from //training set ----- void opf_OPFLearning(Subgraph **sgtrain, Subgraph **sgeval){ int i = 0, iterations = 10; float Acc = FLT_MIN, AccAnt = FLT_MIN,MaxAcc=FLT_MIN, delta; Subgraph *sg=NULL; do{ AccAnt = Acc; fflush(stdout); fprintf(stdout, "\nrunning iteration ... %d ", i); opf_OPFTraining(*sgtrain); opf_OPFClassifying(*sgtrain, *sgeval); Acc = opf_Accuracy(*sgeval); if (Acc > MaxAcc){ MaxAcc = Acc; if (sg!=NULL) DestroySubgraph(&sg); sg = CopySubgraph(*sgtrain); } opf_SwapErrorsbyNonPrototypes(&(*sgtrain), &(*sgeval)); fflush(stdout); fprintf(stdout,"opf_Accuracy in the evaluation set: %.2f %%\n", Acc*100); i++; delta = fabs(Acc-AccAnt); }while ((delta > 0.0001) && (i <= iterations)); DestroySubgraph(&(*sgtrain)); *sgtrain = sg; }
int main(int argc, char **argv) { if (argc != 5) { fprintf(stderr, "\nusage FeatureSelection <training set> <evaluating set> <testing set> <search space configuration file>\n"); exit(-1); } SearchSpace *s = NULL; int i; double time_opt, time_classify, classification_error; timer tic, toc; FILE *f = NULL; TransferFunc optTransfer = NULL; Subgraph *Train = NULL, *Evaluate = NULL, *Merge = NULL, *Test = NULL, *newTrain = NULL, *newTest = NULL; Train = ReadSubgraph(argv[1]); Evaluate = ReadSubgraph(argv[2]); Test = ReadSubgraph(argv[3]); s = ReadSearchSpaceFromFile(argv[4], _WCA_); optTransfer = S2TransferFunction; for (i = 0; i < Train->nfeats; i++) { s->LB[i] = -20; s->LB[i] = 20; } fprintf(stderr, "\nInitializing search space ... "); InitializeSearchSpace(s, _WCA_); fprintf(stderr, "\nOk\n"); fflush(stderr); fprintf(stderr, "\nRunning WCA ... "); gettimeofday(&tic, NULL); runWCA(s, FeatureSelectionOPF, Train, Evaluate, optTransfer); gettimeofday(&toc, NULL); fflush(stderr); fprintf(stderr, "\nOK\n"); time_opt = ((toc.tv_sec - tic.tv_sec) * 1000.0 + (toc.tv_usec - tic.tv_usec) * 0.001) / 1000.0; fprintf(stdout, "\nOptimization time: %f seconds\n", time_opt); fflush(stderr); Merge = opf_MergeSubgraph(Train, Evaluate); fflush(stderr); fprintf(stderr, "\nWriting new training and testing sets ...\n"); newTrain = CreateSubgraphFromSelectedFeatures(Merge, s->g); newTest = CreateSubgraphFromSelectedFeatures(Test, s->g); fprintf(stderr, "\nTraining set\n"); WriteSubgraph(newTrain, "training.wca.dat"); fprintf(stderr, "\n\nTesting set\n"); WriteSubgraph(newTest, "testing.wca.dat"); fflush(stderr); fprintf(stderr, "\nOK\n"); opf_OPFTraining(newTrain); gettimeofday(&tic, NULL); opf_OPFClassifying(newTrain, newTest); gettimeofday(&toc, NULL); classification_error = opf_Accuracy(newTest); time_classify = ((toc.tv_sec - tic.tv_sec) * 1000.0 + (toc.tv_usec - tic.tv_usec) * 0.001) / 1000.0; fprintf(stdout, "\nClassification time: %f seconds\n", time_classify); fflush(stderr); f = fopen("best_feats.txt", "a"); fprintf(f, "%d %d", newTrain->nfeats, (int)s->g[0]); for (i = 1; i < Train->nfeats; i++) { fprintf(f, " %d", (int)s->g[i]); } fprintf(f, "\n"); fclose(f); fprintf(stderr, "\nAccuracy: %.2lf%%\n", 100 * classification_error); f = fopen("final_accuracy.txt", "a"); fprintf(f, "%lf\n", classification_error); fclose(f); fflush(stderr); fprintf(stderr, "\nDeallocating memory ..."); DestroySubgraph(&Train); DestroySubgraph(&Evaluate); DestroySubgraph(&Merge); DestroySubgraph(&Test); DestroySubgraph(&newTrain); DestroySubgraph(&newTest); fflush(stderr); fprintf(stderr, "\nOK\n"); f = fopen("optimization.time", "a"); fprintf(f, "%f %f\n", time_opt, time_classify); fclose(f); DestroySearchSpace(&s, _WCA_); return 0; }
int main(int argc, char **argv) { if (argc != 4) { fprintf(stderr, "\nusage CombinatorialOPF <training set> <testing set> <input combinatorial matrix>\n"); exit(-1); } int i, j, acc_index, m, n; double time_comb, classification_accuracy, overall_accuracy = 0, **r; timer tic, toc; FILE *f = NULL; Subgraph *Train = NULL, *Test = NULL, *newTrain = NULL, *newTest = NULL; Train = ReadSubgraph(argv[1]); Test = ReadSubgraph(argv[2]); fprintf(stderr, "\nInitializing combinatorial OPF ... "); f = fopen(argv[3], "r"); fscanf(f, "%d\n", &n); m = pow(2, n); r = (double **)calloc(m, sizeof(double *)); for (i = 0; i < m; i++) r[i] = (double *)calloc(n, sizeof(double)); for (i = 0; i < m; i++) { for (j = 0; j < n; j++) { fscanf(f, "%lf ", &r[i][j]); } fscanf(f, "\n"); } fclose(f); fprintf(stderr, "\nOk\n"); fflush(stderr); fprintf(stderr, "\nRunning OPF ... "); f = fopen("final_accuracy.txt", "a"); gettimeofday(&tic, NULL); for (i = 0; i < m; i++) { newTrain = CreateSubgraphFromSelectedFeatures(Train, r[i]); newTest = CreateSubgraphFromSelectedFeatures(Test, r[i]); opf_OPFTraining(newTrain); opf_OPFClassifying(newTrain, newTest); classification_accuracy = opf_Accuracy(newTest); fprintf(f, "%lf\n", classification_accuracy); if (classification_accuracy > overall_accuracy) { overall_accuracy = classification_accuracy; acc_index = i; } } gettimeofday(&toc, NULL); fclose(f); fflush(stderr); fprintf(stderr, "\nOK\n"); time_comb = ((toc.tv_sec - tic.tv_sec) * 1000.0 + (toc.tv_usec - tic.tv_usec) * 0.001) / 1000.0; fprintf(stdout, "\nCombination time: %f seconds\n", time_comb); fflush(stderr); f = fopen("best_feats.txt", "a"); fprintf(f, "%d ", n); for (i = 0; i < n; i++) { fprintf(f, "%d ", (int)r[acc_index][i]); } fprintf(f, "\n"); fclose(f); fflush(stderr); fprintf(stderr, "\nDeallocating memory ..."); DestroySubgraph(&Train); DestroySubgraph(&Test); DestroySubgraph(&newTrain); DestroySubgraph(&newTest); fflush(stderr); fprintf(stderr, "\nOK\n"); f = fopen("combination.time", "a"); fprintf(f, "%f\n", time_comb); fclose(f); return 0; }
int main(int argc, char **argv){ fflush(stdout); fprintf(stdout, "\nProgram that executes the training and classification phase of the OPF classifier\n"); fprintf(stdout, "\nIf you have any problem, please contact: "); fprintf(stdout, "\n- [email protected]"); fprintf(stdout, "\n- [email protected]\n"); fprintf(stdout, "\nLibOPF version 2.0 (2009)\n"); fprintf(stdout, "\n"); fflush(stdout); if((argc != 3) && (argc != 2)){ fprintf(stderr, "\nusage opf_train_and_classify <P1> <P2> <P3>"); fprintf(stderr, "\nP1: training set in the OPF file format"); fprintf(stderr, "\nP2: test set in the OPF file format"); fprintf(stderr, "\nP3: precomputed distance file (leave it in blank if you are not using this resource)\n"); exit(-1); } int n, i; char fileName[256]; FILE *f = NULL; timer tic, toc,ticC,tocC; float time, timeC; if(argc == 4) opf_PrecomputedDistance = 1; fprintf(stdout, "\nReading data file ..."); fflush(stdout); Subgraph *g = ReadSubgraph(argv[1]); Subgraph *gTest = ReadSubgraph(argv[1]); fprintf(stdout, " OK"); fflush(stdout); if(opf_PrecomputedDistance) opf_DistanceValue = opf_ReadDistances(argv[3], &n); fprintf(stdout, "\nTraining OPF classifier ..."); fflush(stdout); gettimeofday(&tic,NULL); opf_OPFTraining(g); gettimeofday(&toc,NULL); fprintf(stdout, " OK"); fflush(stdout); fprintf(stdout, "\nClassifying test set ..."); fflush(stdout); gettimeofday(&ticC,NULL); opf_OPFClassifying(g, gTest); gettimeofday(&tocC,NULL); fprintf(stdout, " OK"); fflush(stdout); fprintf(stdout, "\nWriting classifier's model file ..."); fflush(stdout); opf_WriteModelFile(g, "classifier.opf"); fprintf(stdout, " OK"); fflush(stdout); fprintf(stdout, "\nWriting output file ..."); fflush(stdout); sprintf(fileName,"%s.out",argv[1]); f = fopen(fileName,"w"); for (i = 0; i < g->nnodes; i++) fprintf(f,"%d\n",g->node[i].label); fclose(f); fprintf(stdout, " OK"); fflush(stdout); fprintf(stdout, "\nDeallocating memory ..."); fflush(stdout); DestroySubgraph(&g); DestroySubgraph(&gTest); if(opf_PrecomputedDistance){ for (i = 0; i < n; i++) free(opf_DistanceValue[i]); free(opf_DistanceValue); } fprintf(stdout, " OK\n"); time = ((toc.tv_sec-tic.tv_sec)*1000.0 + (toc.tv_usec-tic.tv_usec)*0.001)/1000.0; fprintf(stdout, "\nTraining time: %f seconds\n", time); fflush(stdout); timeC = ((tocC.tv_sec-ticC.tv_sec)*1000.0 + (tocC.tv_usec-ticC.tv_usec)*0.001)/1000.0; fprintf(stdout, "\nTesting time: %f seconds\n", time); fflush(stdout); sprintf(fileName,"%s.time",argv[1]); f = fopen(fileName,"a"); fprintf(f,"%f,%f\n",time,timeC); fclose(f); return 0; }