未完待續

gru_model = K.Sequential()
gru_model.add(K.layers.GRU(units=256, return_sequences=True, input_shape=(7, 4)))
gru_model.add(K.layers.Dropout(0.3214))
gru_model.add(K.layers.GRU(units=64))
gru_model.add(K.layers.Dropout(0.1432))
gru_model.add(K.layers.Dense(units=1, activation='sigmoid'))
gru_model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])

train_data = np.array(train_data)
train_label = np.array(train_label)
split_num = int(len(train_data)*0.8)
train_data, test_data = train_data[:split_num], train_data[split_num:]
train_label, test_label = train_label[:split_num], train_label[split_num:]