随机森林RandomForest实现鸢尾花分类

1. 导入需要的包

from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import RandomForestRegressor
import numpy as np
from sklearn.datasets import load_iris

2. 加载自带数据集

#加载数据集
iris = load_iris()
iris 
#features：萼片长度、萼片宽度、花瓣长度、花瓣宽度
#labels:setosa、vesicolor、virginica

3. 建立随机森林模型

RF = RandomForestRegressor()#默认参数
RF.fit(iris.data,iris.target)

4. 预测

instance = iris.data[[100,109]]#挑两个样本
print("instance 0 prediction is {}".format(RF.predict(instance[[0]])))
print("instance 1 prediction is {}".format(RF.predict(instance[[1]])))
print("instance 0 actually is {}".format(iris.target[100]))
print("instance 1 actually is {}".format(iris.target[109]))