A Novel Explainable Deep Learning Model with Class Specific Features

Abstract

The predictive accuracy of any machine learning model is highly depended on the features used to train the model. For this reason, it is important to extract good discriminative features from the raw data. This extraction of good features from raw data is a challenging task. Deep learning models like Convolutional Neural Networks (CNNs) have the ability to automatically extract features from raw data and also have excellent predictive capabilities. This excellent predictive capability and ability to extract good features from raw data have made CNN very popular, especially in the field of computer vision. Even though CNN is popular, like many other deep learning models it is also notoriously..