ikki_NN_1.py 文件源码

def build_model(self):
            model = Sequential()
            model.add(Dropout(0.2, input_shape=(nn_input_dim_NN,)))
            model.add(Dense(input_dim=nn_input_dim_NN, output_dim=120, init='uniform'))
            model.add(LeakyReLU(alpha=.00001))
            model.add(BatchNormalization())
            model.add(Dropout(0.5))
            model.add(Dense(input_dim=120,output_dim=280, init='uniform'))
            model.add(LeakyReLU(alpha=.00001))
            model.add(BatchNormalization())
            model.add(Dropout(0.5))
            model.add(Dense(input_dim=280,output_dim=100, init='uniform', activation='relu'))
            model.add(BatchNormalization())
            model.add(Dropout(0.4))
            model.add(Dense(input_dim=100,output_dim=2, init='uniform', activation='softmax'))    
            #model.add(Activation('softmax'))
            sgd = SGD(lr=0.015, decay=1e-6, momentum=0.9, nesterov=True)

            model.compile(optimizer=sgd, loss='binary_crossentropy',class_mode='binary')

            return KerasClassifier(nn=model,**self.params)