ikki_NN_1.py 文件源码

def build_model(self):
            model = Sequential()
            model.add(Dropout(0.1, input_shape=(nn_input_dim_NN,)))
            model.add(Dense(input_dim=nn_input_dim_NN, output_dim=310, init='he_normal'))
            model.add(LeakyReLU(alpha=.001))
            model.add(BatchNormalization())
            model.add(Dropout(0.6))
            model.add(Dense(input_dim=310,output_dim=252, init='he_normal'))
            model.add(PReLU(init='zero'))
            model.add(BatchNormalization())
            model.add(Dropout(0.5))
            model.add(Dense(input_dim=252,output_dim=128, init='he_normal'))
            model.add(LeakyReLU(alpha=.001))
            model.add(BatchNormalization())
            model.add(Dropout(0.4))
            model.add(Dense(input_dim=128,output_dim=2, init='he_normal', activation='softmax'))
            #model.add(Activation('softmax'))
            sgd = SGD(lr=0.02, decay=1e-6, momentum=0.9, nesterov=True)

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

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