Hybridization of Apriori Algorithm and Genetic Algorithm for Association Rule Mining in Generative AI Enabled Machine Learning

Machine learning (ML) is software technology which exploits Generative Artificial Intelligence (GAI) to train sophisticated advance software applications, which are capable to learn from Big Data Analysis for excellent performance, which gets more precise with repetitive training and software experience. Generative AI is a category of artificial intelligence technique that can generates different types of text content, suggestions and idea based images and voice. GAI frequently uses Apriori Algorithm (APAL) for Association Rule Mining in Big Data Investigation, Analysis and Result Generation. Computational Complexity, Noise Sensitivity and Computational time are three major vulnerabilities which Apriori Algorithm inherits in big data applications. Article suggests an advance algorithm, which is hybridization of Apriori Algorithm and Genetic Algorithm to address the noticed vulnerabilities. Test simulation is done in AI Tool Kit of Simulink in MATLAB 7.6 Virtual Simulation Environment.