LSTM

LSTM.py

    def LSTM(self):
        model = Sequential()
        model.add(Embedding(self.vocab_length, 30, input_length=self.max_len))
        model.add(LSTM(200))
        model.add(Dense(self.max_len, activation='relu', W_regularizer=l2(0.90)))
        model.add(Dense(self.tr_labels.shape[1], activation='softmax', W_regularizer=l2(0.1)))
        adam_1 = Adam(lr=0.008)
        model.compile(loss='categorical_crossentropy', optimizer=adam_1,metrics=['accuracy'])
        model.summary()
        self.model = model