Esempio n. 1
0
def usekNN(path):
	print "step1: load data..."
	train_x, train_y = loadDataSet()
	
	print "step 2: caculating..."
	items = kNNClassify(handle(path), train_x, train_y, 3)
	pitems = kNNClassify(handle(path), train_x, train_y, 50)
	print "the answer is:",
	print items[0][0]
	print "the possible answers are(include answer):",
	for i, item in enumerate(pitems):
		print item[0],
	print ""
Esempio n. 2
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def useSVM(path):
	print "step 1: load data..."
	train_x, train_y, test_x, test_y = loadDataSetForTest()
	print "step 2: train..."
	m = SVMTrain(train_y, train_x)
	print "step 3: caculating..."
	print "the answer is:",
	print SVMPredict([], handle(path), m, False)[0]
Esempio n. 3
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def useBayes(path):
	print "step1: load data..."
	train_x, train_y = loadDataSet()
	print "step 2: train..."
	pv, pa = trainNB0(train_x, train_y)		
	print "step 3: caculating..."
	items = classifyNB(handle(path), pv, pa)
	print "the answer is:",
	print items[0][0]
	print "the possible answers are(include answer):",
	for i, item in enumerate(items):
			print item[0],	
	print ""