装了一天sklearn环境，之前已经装好numpy，scipy……，但是还有各种问题，最后用Anaconda搞定，官网下载速度太慢，存到网盘分享一下

在Anaconda的shell下pip list看一下安装好的包，import sklearn测试，pycharm调用

pycharm中添加Anaconda

sklearn测试代码

# Import the necessary modules and libraries

import numpy as np

from sklearn.tree import DecisionTreeRegressor

import matplotlib.pyplot as plt

# Create a random dataset

rng = np.random.RandomState(1)

X = np.sort(5 * rng.rand(80, 1), axis=0)

y = np.sin(X).ravel()

y[::5] += 3 * (0.5 - rng.rand(16))

# Fit regression model

regr_1 = DecisionTreeRegressor(max_depth=2)

regr_2 = DecisionTreeRegressor(max_depth=5)

regr_1.fit(X, y)

regr_2.fit(X, y)

# Predict

X_test = np.arange(0.0, 5.0, 0.01)[:, np.newaxis]

y_1 = regr_1.predict(X_test)

y_2 = regr_2.predict(X_test)

# Plot the results

plt.figure()

plt.scatter(X, y, c="darkorange", label="data")

plt.plot(X_test, y_1, color="cornflowerblue", label="max_depth=2", linewidth=2)

plt.plot(X_test, y_2, color="yellowgreen", label="max_depth=5", linewidth=2)

plt.xlabel("data")

plt.ylabel("target")

plt.title("Decision Tree Regression")

plt.legend()

plt.show()

输出结果

决策树回归结果