How can I teach a model using single class in machine learning using Keras?

Question

I am new to machine learning and currently got a good start in binary and multi-class model development using Keras. Now I would like to learn how I could teach a model for outlier image detection. I used the binary classification method to teach the outlier class by separating the outlier class from other image class. This method does not work as soon as I give an image that was not during teaching and the outcome is totally unpredictable.

1. Where should I start this?
2. Is there any online tutorial(s) I could follow?

Answer 1

There isn't such a thing as single-class classification. Your problem is binary since you are differentiating between two classes (normal, outlier).

Having said that, your problem might be too little data for the outliers. Unbalanced classes might not produce good results so you should try that first. The second problem might be the model's parameters not having the right values, this requires some experimentation on your part.

I can't say much since the problem is so vague. If you want to post some code and some results I could tell more.