python|AdaBoost(AdaBoostClassifier)_adaboostclassifier()

# -*- coding: utf-8 -*-
"""
Created on Thu Nov  7 15:49:21 2019
@author: weiping
"""
 
from sklearn.ensemble import AdaBoostClassifier as abc
from sklearn.ensemble import AdaBoostRegressor as abr
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 = abc()
rf.fit(x_tr,y_tr)
rf_p = rf.predict(x_te)
f_importances = rf.feature_importances_ #特征的重要性
imp = pd.Series(f_importances,index = list('abcd')) #画出特征重要程度的条形图
plt.barh(imp.index,imp.values)
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 = abr()
rfr.fit(x_tr,y_tr)
rf_p = rfr.predict(x_te)
imp = pd.Series(rfr.feature_importances_,index = list('abcdefghijklm'))
plt.barh(imp.index,imp.values)
metrics.r2_score(rf_p,y_te)

参数（https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostClassifier.html#sklearn.ensemble.AdaBoostClassifier）