ValueError: Error when checking : expected dense_1_input to have shape (3,) but got array with shape (1,)

Question

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\'         


        

Answer 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.