Applied Intelligent Decision Making in Machine Learning

Decision making is the process of selection of best choice made logically from the accessible options. Decision making analyzes the large volume of data in a particular field and is a very difficult task to do manually. A technique must be used to find out the possible outcome of each option available. It also determines the option that is best at a particular moment for an effective decision-making process. Machine learn- ing uses a set of mathematical models and algorithms for the construction of a deci- sion-making system that gradually improves its performance on specific tasks. It is also based on a model that develops intelligent, adaptive, and hybrid tools and meth- ods for solving complex decision-making problems. Artificial intelligence has already been recognized as a standard tool for the decision-making process. Despite several such developments, many findings still need to be addressed due to the advancement of technologies such as artificial intelligence, machine learning, and information technology. The computer system should analyze dynamically each option as well as alternatives to make an appropriate intelligent decision. This book will also specifically focus on applied intelligent decision-making fields that perform various tasks effectively for predictive analysis, classification, clustering, feature selection, feature reduction, recommendations, information retrieval, and pattern rec- ognition in a very limited amount of time with high performance.