MACHINE LEARNING MODEL FOR PREDICTING STUDENTS’ ABSENCES
The paper considers the issues of software implementation of a machine learning model capable of predicting student attendance based on pre-collected real data generated by polling and statistical analysis. In this paper, a decision tree learning algorithm based on the use of a tree graph was used. The software implementation of the algorithm is based on calculating the probability of occurrence of an event, the advantage lies in structuring and systematizing the problem, and the final decision is made based on logical conclusions. The main task is to find an answer to the question whether it is possible to solve the problem of predicting student attendance using machine learning methods, and if possible, then determine the accuracy of this forecast.