I am working on a regression task, using cnn for feature extraction and fully-connected layers for generating regression values.
However, the target value of each input data is an integer. There are five possible target values: 1 representing 'hate', 2 representing 'dislike', ... , and the final target value 5 representing 'love'. (I know the task can also be considered as a classification task, but I need to implement it as a regression task.)
The evaluation metrics are rmse and mae. I want to make the DNN generate intergers as regression results, which can make the evaluation metrics better. At present, the DNN network will generate for example 4.012 for target value 4. (Is there any other method than threshold? Or any method for learning the threshold automatically at the same time?. I am thinking about adding a classification layer connected to the second hidden layer to help the network learn the interger constraint.)