The naÏve bayes algorithm for learning data analytics

Abstract

The field of data science analysis in artificial intelligence is being deeply interested by many scientists around the world, many techniques are proposed to improve accuracy from Naive Bayes model by reducing the problem of interdependence between its attributes. The new research of this paper, which is presented step by step by the Naive Bayes (NB) method, is the method of applying NB with a new set of attributes. It is worthy of consideration that using learning data analytics method is receiving increased attention, because of the importance of learning data analytics, in order to provide predictive learning results of learners or offer better solutions to support schools to strengthen educational measures or have optimal plans to increase student retention rates studying at the school, as well as help students succeed in their studies. Data related to student management and training activities are collected from softwares, student affairs and learning management systems are operating in practice such as Edusoft.Net software, Moodle and Microsoft Teams, student attendance system by FaceID face recognition… Research, evaluate and select a number of new data technologies for the purpose of building student digital profile, including document storage functions, specifically intelligent functions such as creating, processing and storing documents.