I am designing a 1-dimensional convolution network using keras. In my dataset, I have 29 outputs (y_test), which means for every set of features we get 29 outputs. Does the evaluation function work through all of them? I want to know how the MAE (Mean Average Error) is calculated and returned for all these outputs.
y_test has 29 values for each X data.
[loss_cnn, mse_cnn, mae_cnn] = model_conv1D.evaluate(test_data_reshaped, y_test, verbose=0)
