METHOD FOR DETECTING NON-PROBLEM DOMAIN DATA IN A MACHINE LEARNING MODEL

A method is provided for detecting non-problem domain (NPD) data in a machine learning (ML) model. The method includes training the ML model using problem domain (PD) training data. A second fully connected layer is added to the trained ML model in parallel with a first fully connected layer in the trained ML model. The trained ML model is retrained with NPD training data while preventing weights in the ML model from changing except for weights of the second fully connected layer. An inference operation is performed with the retrained ML model. Output vectors are received from the first and second fully connected layers via a Softmax layer. A metric is computed using the output vectors. The metric is compared to a threshold metric to determine if input samples are PD or NPD. An indication is provided when NPD data is detected. In another embodiment, a ML model is provided.