Decision Making and Machine Learning Algorithms’ Selection with Artificial Intelligent Rule-Based Expert System

Abstract

Everybody is confronted daily with cluster of decisions that must be appropriately taken in the process of making accurate decision; individuals are faced with and most often fall prey to series of common biases, fallacies, and many other decision making odds. In determining which algorithm to apply for analysis (with machine learning algorithms/models) open to critical steps to be taken and also highly depend on many factors ranging from the type of problem at hand, the condition to choose a model and to the expected outcomes. The study looks at how artificial intelligent approach with expert system would be helpful in making timely decision on which type of algorithm(s) is/are capable to be applied and implemented to have desired results. The study also uses VisiRule software to model series of successful channels to arrive at a good decision making means. The use of VisiRule (Artificial Intelligent Based Expert System) was employed to give directional path ways to the selection of appropriate algorithms from supervised and unsupervised machine learning to different classification methods, regression methods, clustering approaches, dimensionality reduction methods, and association rules. The outcome of this study demonstrates the easy way through paths to select relevant and most appropriate model or algorithm that best fit the analysis at hand with detailed explanation of each alternative option. The use of VisiRule software has proven the easy way to achieve decision making problems without any codes requirement for such actions. Decision making challenges could be resolved by just implementing artificial intelligent rule-based expert system which require less time, coding free, and highly achievable accurate outcomes.