1 问题
使用python的机器学习库sklearn实现常见的机器学习分类算法,如决策树、随机森林等。
2 代码实现
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
| import time from sklearn.tree import DecisionTreeClassifier from sklearn.ensemble import RandomForestClassifier import numpy as np
def rf_train(): api_train = np.array([[1, 2, 3], [1, 2, 2]]) type_train = np.array([1, 0]) api_test = np.array([[1, 2, 1]]) type_test = np.array([0])
clf = DecisionTreeClassifier(random_state=0) rfc = RandomForestClassifier(random_state=0) clf = clf.fit(api_train, type_train) rfc = rfc.fit(api_train, type_train) score_c = clf.score(api_test, type_test) score_r = rfc.score(api_test, type_test)
print("Single Tree:{}".format(score_c), "Random Forest:{}".format(score_r))
if __name__ == '__main__': start = time.time() print('最终版-随机森林')
end = time.time() print((end - start) / 60, "min")
|
X 参考