代码如下:
from sklearn.datasets import load_breast_cancer
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import GridSearchCV
from sklearn.model_selection import cross_val_score
import matplotlib.pyplot as plt
# noinspection PyUnresolvedReferences
import pandas as pd
import numpy as np
data = load_breast_cancer()
scorel = []
for i in range(0, 200, 10):
rfc = RandomForestClassifier(n_estimators=i + 1,
n_jobs=-1,
random_state=90)
score = cross_val_score(rfc, data.data, data.target, cv=10).mean() # 交叉验证
scorel.append(score)
print(max(scorel), (scorel.index(max(scorel)) * 10) + 1)
plt.figure(figsize=[20, 5])
plt.plot(range(1, 201, 10), scorel)
plt.show()