代码实现[Python]

# -*- coding: utf-8 -*- 
print(__doc__)

# 码农: Nelle Varoquaux 
#         Alexandre Gramfort 
# 协议: BSD

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

from sklearn.linear_model import LinearRegression
from sklearn.isotonic import IsotonicRegression
from sklearn.utils import check_random_state

n = 100
x = np.arange(n)
rs = check_random_state(0)
y = rs.randint(-50, 50, size=(n,)) + 50. * np.log1p(np.arange(n))

# #############################################################################
# 拟合IsotonicRegression和LinearRegression models模型

ir = IsotonicRegression()

y_ = ir.fit_transform(x, y)

lr = LinearRegression()
lr.fit(x[:, np.newaxis], y)  # x needs to be 2d for LinearRegression

# #############################################################################
# 绘图展示结果

segments = [[[i, y[i]], [i, y_[i]]] for i in range(n)]
lc = LineCollection(segments, zorder=0)
lc.set_array(np.ones(len(y)))
lc.set_linewidths(np.full(n, 0.5))

fig = plt.figure()
plt.plot(x, y, 'r.', markersize=12)
plt.plot(x, y_, 'b.-', markersize=12)
plt.plot(x, lr.predict(x[:, np.newaxis]), 'b-')
plt.gca().add_collection(lc)
plt.legend(('Data', 'Isotonic Fit', 'Linear Fit'), loc='lower right')
plt.title('Isotonic regression')
plt.show()

代码执行

代码运行时间大约:0分0.056秒。
运行代码输出的图片内容如下:

源码下载

• Python版源码文件: plot_isotonic_regression.py
• Jupyter Notebook版源码文件: plot_isotonic_regression.ipynb

参考资料

• Isotonic Regression