Error When Checking Target: Expected Dense_2 To Have 2 Dimensions, But Got Array With Shape (1, 1226, 2)

Here is the code that I am trying to run: y = Df[['label']] y_train = np.column_stack((y_train['label'])) y_test = np.column_stack((y_test['label'])) data_dim = 18 timesteps =

Solution 1:

It seems you are doing binary classification. Therefore, there are a few things that need to be fixed:

1. The y_train should consists of zeros and ones. The following would convert all the -1 labels to zeros:

   y_train = (y_train == 1).astype('float32')
   

2. Reshape the labels to have a shape of (n_samples, 1):

   y_train = y_train.reshape(-1, 1)
   

3. Use 'sigmoid' as the activation of last layer:

   model.add(Dense(1, activation='sigmoid'))
   

Solution 2:

You should use 'sigmoid' activation function for the last layer, because it is binary classification