python|随机森林（RandomForestClassifier）

# -*- coding: utf-8 -*-
"""
Created on Wed Nov  6 16:23:18 2019

@author: weiping
"""

from sklearn.ensemble import RandomForestClassifier as rfc
from sklearn.ensemble import RandomForestRegressor as rfr
import pandas as pd
import numpy as np
import sklearn.datasets as skdata
import matplotlib.pyplot as plt
from sklearn.model_selection  import train_test_split
from sklearn import metrics

'''分类'''
data_x,data_y = skdata.load_iris().data, skdata.load_iris().target

df = pd.DataFrame(data_x,columns = list('abcd'))
df['f'] = data_y
x_tr,x_te,y_tr,y_te = train_test_split(df[list('abcd')],df['f'],train_size = 0.7,random_state =22)

rf = rfc()
rf.fit(x_tr,y_tr)
rf_p = rf.predict(x_te)

metrics.confusion_matrix(y_te,rf_p)

'''回归'''
d_x ,d_y = skdata.load_boston().data,skdata.load_boston().target

x_tr,x_te,y_tr,y_te = train_test_split(d_x,d_y,train_size = 0.7,random_state = 22)

rfr = rfr()
rfr.fit(x_tr,y_tr)
rf_p = rfr.predict(x_te)

metrics.r2_