随机森林准确率和分类器关系

#!/usr/bin/python
# -*- coding:utf-8 -*-

import operator
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
from functools import reduce
from scipy.special import comb
print('comb(10, 2) = ', comb(100, 30))


def c(n, k): return reduce(operator.mul, list(range(n-k+1, n+1))) / reduce(operator.mul, list(range(1, k+1)))


def bagging(n, p): s = 0 for i in range(n // 2 + 1, n + 1): s += comb(n, i) * p ** i * (1 - p) ** (n - i) return s


if __name__ == "__main__": n = 100 x = np.arange(1, n, 2) y = np.empty_like(x, dtype=np.float) for i, t in enumerate(x): y[i] = bagging(t, 0.6) if t % 10 == 9: print(t, '个分类器的正确率：', y[i]) mpl.rcParams['font.sans-serif'] = 'simHei' mpl.rcParams['axes.unicode_minus'] = False plt.figure(facecolor='w'
  

 

  
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文章来源: maoli.blog.csdn.net，作者：刘润森！，版权归原作者所有，如需转载，请联系作者。

原文链接：maoli.blog.csdn.net/article/details/89457493