Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics

In Mohammadi et al. (Evolutionary computation, optimization and learning algorithms for data science. arXiv preprint, arXiv: 1908.08006, 2019), we have explored the theoretical aspects of feature selection and evolutionary algorithms. In this chapter, we focus on optimization algorithms for enhancing data analytic process, i.e., we propose to explore applications of nature-inspired algorithms in data science. Feature selection optimization is a hybrid approach leveraging feature selection techniques and evolutionary algorithms process to optimize the selected features. Prior works solve this problem iteratively to converge to an optimal feature subset. Feature selection optimization is a non-specific domain approach.