Valueerror: Error When Checking : Expected Dense_1_input To Have Shape (3,) But Got Array With Shape (1,)

I am trying to predict using the learned .h5 file. The learning model is as follows. model =Sequential() model.add(Dense(12, input_dim=3, activation='relu')) model.add(Dense(8, act

Solution 1:

The shape of x is obviously (3,1), but the above error continues.

You are right, but that's not what keras expects. It expects (1, 3) shape: by convention, axis 0 denotes the batch size and axis 1 denotes the features. The first Dense layer accepts 3 features, that's why it complains when it sees just one.

The solution is simply to transpose x.