python|随机森林（RandomForestClassifier）

最新推荐文章于 2024-09-26 08:40:05 发布

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最新推荐文章于 2024-09-26 08:40:05 发布 · 3.7k 阅读

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本文深入探讨Python中scikit-learn库的RandomForestClassifier，介绍如何使用该模型进行分类任务，包括其核心参数的解释和调整技巧。

# -*- 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_