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)
