scikit-learnのfit()メソッドを使う

いきなりコードから始めます。

from sklearn import svm

xor_data = [
		[0, 0, 0],
		[0, 1, 1],
		[1, 0, 1],
		[1, 1, 0]
] 

data = []
label = []
for row in xor_data:
	p = row[0]
	q = row[1]
	r = row[2]
	data.append([p, q])
	label.append(r)

clf = svm.SVC()
clf.fit(data, label)

pre = clf.predict(data)
print("予測結果:", pre)

ok = 0; total = 0
for idx, answer in enumerate(label):
	p = pre[idx]
	if p == answer: ok += 1
	total += 1
print("正解率:", ok, "/", total, "=", ok/total)

続いてコマンドライン
[vagrant@localhost python]$ python3 app.py
/home/vagrant/.pyenv/versions/3.5.2/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
/home/vagrant/.pyenv/versions/3.5.2/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
/home/vagrant/.pyenv/versions/3.5.2/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
/home/vagrant/.pyenv/versions/3.5.2/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
予測結果: [0 1 1 0]
正解率: 4 / 4 = 1.0

なんだこりゃ、いきなり一気に難易度が上がった？！
scikit-learn　－＞　Pythonの機械学習ライブラリ