# -*- coding: utf-8 -*- ''' Created on 2018年1月18日 @author: Jason.F @summary: GridSearch網(wǎng)格搜索：同一模型下組合參數(shù)選擇最優(yōu)； 嵌套交叉驗(yàn)證：不同模型選擇最優(yōu)； ''' import pandas as pd from sklearn.preprocessing import LabelEncoder from sklearn.cross_validation import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.pipeline import Pipeline from sklearn.grid_search import GridSearchCV from sklearn.svm import SVC import numpy as np from sklearn.model_selection import cross_val_score from sklearn.tree import DecisionTreeClassifier #導(dǎo)入數(shù)據(jù) df = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data',header=None) X=df.loc[:,2:].values y=df.loc[:,1].values le=LabelEncoder() y=le.fit_transform(y)#類標(biāo)整數(shù)化 print (le.transform(['M','B'])) #劃分訓(xùn)練集合測試集 X_train,X_test,y_train,y_test = train_test_split (X,y,test_size=0.20,random_state=1) #建立pipeline pipe_svc=Pipeline([('scl',StandardScaler()),('clf',SVC(random_state=1))]) param_range=[0.0001,0.001,0.01,0.1,1.0,10.0,100.0,1000.0] param_grid=[{'clf__C':param_range,'clf__kernel':['linear']},\{'clf__C':param_range,'clf__gamma':param_range,'clf__kernel':['rbf']}] #網(wǎng)格搜索 gs=GridSearchCV(estimator=pipe_svc,param_grid=param_grid,scoring='accuracy',cv=10,n_jobs=1) gs=gs.fit(X_train,y_train) print (gs.best_score_) print (gs.best_params_) #選擇最佳模型 clf=gs.best_estimator_ clf.fit(X_train,y_train) print ('Test accuracy:%.3f' % clf.score(X_test,y_test))#嵌套交叉驗(yàn)證 gs_svm=GridSearchCV(estimator=pipe_svc,param_grid=param_grid,scoring='accuracy',cv=10,n_jobs=1)#-1 scores_svm=cross_val_score(gs_svm,X,y,scoring='accuracy',cv=5) print ('SVM CV accuracy:%.3f +/- %.3f'%(np.mean(scores_svm),np.std(scores_svm)))#比較決策樹交叉驗(yàn)證 gs_dt=GridSearchCV(estimator=DecisionTreeClassifier(random_state=0),param_grid=[{'max_depth':[1,2,3,4,5,6,7,None]}],scoring='accuracy',cv=5) scores_dt=cross_val_score(gs_dt,X,y,scoring='accuracy',cv=5) print ('DT CV accuracy:%.3f +/- %.3f'%(np.mean(scores_dt),np.std(scores_dt)))

結(jié)果：

[1 0] 0.978021978022 {'clf__C': 0.1, 'clf__kernel': 'linear'} Test accuracy:0.965 SVM CV accuracy:0.972 +/- 0.012 DT CV accuracy:0.917 +/- 0.009

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