机器学习入门-决策树使用实例(代码)

from sklearn import tree
from sklearn.cross_validation import train_test_split

# 数据拆分
train_x, test_x, train_y, test_y = train_test_split(housing.data, housing.target, test_size=0.1, random_state=42)
# 建立决策树
dtr = tree.DecisionTreeRegressor(random_state=42)
# 训练数据
dtr.fit(train_x, train_y)
# 打印出dtr得分, 这里的得分表示的是准确率
print(dtr.score(test_x, test_y))

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转载自www.cnblogs.com/my-love-is-python/p/10280627.html