10.5.4 利用sklearn搭建多层神经网络
作者:互联网
from sklearn.datasets import load_wine wine=load_wine() wine.data[0] wine.data.shape wine.target_names wine.feature_names X=wine.data y=wine.target from sklearn.model_selection import train_test_split X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3,random_state=0) from sklearn.neural_network import MLPClassifier model=MLPClassifier(solver="lbfgs",hidden_layer_sizes=(100,)) model.fit(X_train,y_train) y_predict_on_train=model.predict(X_train) y_predict_on_test=model.predict(X_test) from sklearn.metrics import accuracy_score print('训练集的准确率为:{:.2f}%'.format(100*accuracy_score(y_train,y_predict_on_train))) print('测试集的准确率为:{:.2f}%'.format(100*accuracy_score(y_test,y_predict_on_test)))
标签:10.5,predict,神经网络,train,test,model,sklearn,wine 来源: https://www.cnblogs.com/redufa/p/14424026.html