def PrintResults(results, resultsFile, featureFile): demo_utils.print_results(results, resultsFile); print results.getLog(); print results.getSuccessRate #Find features demo_utils.find_features(trainData, featureFile);
def PrintResults(results, resultsFile, featureFile): demo_utils.print_results(results, resultsFile) print results.getLog() print results.getSuccessRate #Find features demo_utils.find_features(trainData, featureFile)
for C in Cs: print "**** Train/Test with K1: " + str(k1) + ", k2: " + str(k2) + ", C: " + str(C) trainData = generate_model.get_spectrum_data(trainSeqFile, k1, k2, trainLen, trainLen, True) folds = [] s = svm.SVM(C=C) s.train(trainData) # testData = SparseDataSet(testFeatureFile); testData = demo_utils.get_spectrum_data(testSeqFile, k1, k2, testLen, testLen, True) results = s.test(testData) labels = results.getGivenClass() dvals = results.getDecisionFunction() folds.append((dvals, labels)) demo_utils.print_results(results) print "Results Log: " results.getLog() fpc, tpc, area = roc_mod.roc_VA(folds, None) print "Area: " + str(area) if area > bestAUC: bestAUC = area bestFP = fpc bestTP = tpc bestC = C ofile = open("roc%s.txt" % (str(C)), "w") ofile.write("area: " + str(area) + "\n") ofile.write("bestFP: " + str(bestFP) + "\n") ofile.write("bestTP: " + str(bestTP) + "\n") ofile.write("bestC: " + str(bestC) + "\n") ofile.close()
def inDomainTest(trainModelFile, trainSpectrumData, testSpectrumData, resultsFile): new_svm = SVM() new_svm.load(trainModelFile, trainSpectrumData) results = new_svm.test(testSpectrumData) demo_utils.print_results(results, resultsFile)