One Aggregated Approach in Multidisciplinary Based Modeling to Predict Further Students’ Education

Abstract

In this paper, one multidisciplinary-applicable aggregated model has been proposed and verified. This model uses traditional techniques, on the one hand, and algorithms of machine learning as modern techniques, on the other hand, throughout the determination process of the relevance of model attributes for solving any problems of multicriteria decision. The main goal of this model is to take advantage of both approaches and lead to better results than when the techniques are used alone. In addition, the proposed model uses feature selection methodology to reduce the number of attributes, thus increasing the accuracy of the model. We have used the traditional method of regression analysis combined with the well-known mathematical method Analytic Hierarchy Process (AHP). This approach has been combined with the application of the ReliefF classificatory modern ranking method of machine learning. Last but not least, the decision tree classifier J48 has been used for aggregation purposes. Information on grades of the first-year graduate students at the Criminalistics and Police University, Belgrade, after they chose and finished one of the three possible study modules, was used for the evaluation of the proposed model. To the best knowledge of the authors, this work is the first work when considering mining closed frequent trees in case of the streaming of time-varying data.

An Asymmetric Ensemble Method for Determining the Importance of Individual Factors of a Univariate Problem

“…Namely, the required time for its execution, which is evidently longer than the time required if only one of the algorithms aggregated in the proposed ensemble was used, is not a limitation for working in real time, which is valid for considered problem. of human life, such as traffic and education, which were also considered as problems in the literature [101,102].…”

An Ensemble Method for Determining the Importance of Selected Social and Health Factors Affecting the Inpatient Treatment Quality

“…From other site from planed research in technique and methodology for solving considered healthcare problem and problems in healthcare which already was subject of research of authors [114,115] authors will deal in feature with other from many different problems in healthcare and other fields of human life as for example traffic and education which the authors have already done [116,117].…”

Predicting Math Performance in High School Students using Machine Learning Techniques

“…By acting as an early warning system, these predictive models enable the implementation of focused support measures and intervention techniques to enhance student learning outcomes [1]. Machine learning algorithms and data mining techniques are commonly utilized in student performance prediction modeling [2]. These techniques analyze various attributes such as grades, educational background, psychological evaluation, and demographics to generate predictions about a student's future performance [3].…”

“…They showed that their technique can improve the performance of student performance prediction models. Ranđelović et al [2] proposed a multidisciplinary-applicable aggregated model based on analytic hierarchy process and ReliefF classifier to predict further students' education. Xu et al [8] introduced a two-layer machine learning architecture consisting of multiple base predictors and a set of ensemble classifiers to predict student performance in degree programs.…”