# -*- coding:utf-8 -*-
# Author：hankcs
# Date: 2018-06-20 10:02
# 《自然语言处理入门》5.2 线性分类模型与感知机算法
# 配套书籍：http://nlp.hankcs.com/book.php
# 讨论答疑：https://bbs.hankcs.com/
import matplotlib.pyplot as plt
import matplotlib.lines as mlines
plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号
def newline(p1, p2, color=None, marker=None):
"""
https://stackoverflow.com/questions/36470343/how-to-draw-a-line-with-matplotlib
:param p1:
:param p2:
:return:
"""
ax = plt.gca()
xmin, xmax = ax.get_xbound()
if (p2[0] == p1[0]):
xmin = xmax = p1[0]
ymin, ymax = ax.get_ybound()
else:
ymax = p1[1] + (p2[1] - p1[1]) / (p2[0] - p1[0]) * (xmax - p1[0])
ymin = p1[1] + (p2[1] - p1[1]) / (p2[0] - p1[0]) * (xmin - p1[0])
l = mlines.Line2D([xmin, xmax], [ymin, ymax], color=color, marker=marker)
ax.add_line(l)
return l
if __name__ == '__main__':
male = [1, 1]
female = [0, 1]
fig, ax = plt.subplots()
m = ax.scatter(male[0], male[1], s=60, c='blue', marker='x')
ax.annotate('沈雁冰', male)
f = ax.scatter(female[0], female[1], s=60, c='red', marker='o')
ax.annotate('冰心', female)
ax.legend((m, f), (' 男', ' 女'))
plt.xlim(-0.1, 1.5)
plt.ylim(-0.1, 1.5)
plt.xticks([0, 1])
plt.yticks([0, 1])
plt.title('性别分类问题')
newline([0.5, 0], [1, 1.5])
ax.annotate('3x-y-1.5=0', [0.75, 0.6])
plt.xlabel('特征1：是否含“雁”')
plt.ylabel('特征2：是否含“冰”')
plt.show()
