RF随机森林

 

RF随机森林学习示例：

from sklearn.datasets import load_iris
from sklearn.ensemble import BaggingClassifier
from sklearn.svm import SVC
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score
import numpy as np

iris = load_iris()
X = iris.data
y = iris.target

# SVC()分类器模型为线性支持向量机
# n_estimators=500重复取样500次送入分类器模型训练，得到500个SVC训练模型
# bootstrap=True有放回抽样
# max_samples=0.8，为小数时每次取总样本*max_samples，为整数时每次取max_samples个样本
bag_clf = BaggingClassifier(SVC(), n_estimators=500, boo