def main(): # define the question # and question column set problem = 2 csv = 'project510Data.csv' dataTotal = dTools.dataTotal(csv) q = qTools.Question(problem) q.getInputDataAndLabels(dataTotal._dataList) dataQ = dTools.dataQuestion(q, 0.90) nRuns = 10 allRuns = [] print "----" for ratio in range(950, 1000, 50): dataQ = dTools.dataQuestion(q, 1.0 * ratio / 1000) for maxIter in range(100, 300, 25): print "RATIO:", 1.0 * ratio / 1000 print "MAX ITER: %d" % (maxIter) classifier = aiTools.classifier(q, dataQ, aiTools.featureExtractor, maxIter) allRuns.append((avgNruns(dataQ, classifier, nRuns), 1.0 * ratio / 1000, maxIter)) print "--" print "----" allRuns.sort() print "TOP 15 RUNS:" for x in allRuns[-14:][::-1]: print x
def main(): # define the question # and question column set problem = 2 csv = 'project510Data.csv' dataTotal = dTools.dataTotal(csv) q = qTools.Question(problem) q.getInputDataAndLabels(dataTotal._dataList) trainToTestRatio = 0.9 dataQ = dTools.dataQuestion(q, trainToTestRatio) classifier = aiTools.classifier(q, dataQ, aiTools.featureExtractor, maxIter) classifier.prepDataTrain() classifier.train() tests.append(classifier.test())
def main(): # define the question # and question column set problem = 2 csv = 'project510Data.csv' dataTotal = dTools.dataTotal(csv) q = qTools.Question(problem) q.getInputDataAndLabels(dataTotal._dataList) trainToTestRatio = 0.9 dataQ = dTools.dataQuestion(q, trainToTestRatio) nRuns = 10 classifier = aiTools.classifier(q, dataQ, aiTools.featureExtractor, maxIter) avgNruns(dataQ, classifier, nRuns)
print "\nPROBLEM %d\t%d\t%.2f\nOver %d runs, accuracy averaged: %.2f%s\n" % ( problem, MAX_ITER, RATIO / 100.0, len(runs), avg * 100, "%") allRuns.append((avg, MAX_ITER, RATIO / 100.0)) allRuns.sort() allRuns = allRuns[-14:] del classifier del manager, return_dict, p, proc, runs del dataQ print "TOP 15 RUNS:" for x in allRuns[::-1]: print x csv = 'project510Data.csv' dataTotal = dTools.dataTotal(csv) manager = multiprocessing.Manager() tasks = manager.Queue() num_processes = 1 pool = multiprocessing.Pool(num_processes) processes = [] for i in range(num_processes): process_name = 'P%i' % i new_process = multiprocessing.Process(target=main, args=( i + 1, dataTotal, )) new_process.daemon = False