Autonomic Feature Selection using Computational Intelligence

This paper introduces an autonomic method to optimize Feature Selection (FS) in autonomic systems while also presenting a taxonomy of FS techniques. Feature selection is a dimension reduction technique that has been proven to lead to improved performance by avoiding overfitting and to address complexity, thus providing faster and cost-effective algorithms. To be successful, the current FS methods are heavily reliant on two key elements: (1) a...