One Aggregated Approach in Multidisciplinary Based Modeling to Predict Further Students’ Education
Само за регистроване кориснике
2022
Аутори
Ranđelović, MilanAleksić, Aleksandar
Radovanović, Radovan
Stojanović, Vladica
Čabarkapa, Milan
Ranđelović, Dragan
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
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. I...nformation 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.
Кључне речи:
theory of mathematical modeling / applied mathematics / classification and discrimination / multicriteria decision making / linear regression / prediction theoryИзвор:
Mathematics, 2022, 10, 14, 2381-Издавач:
- Basel : MDPI
Институција/група
JakovTY - JOUR AU - Ranđelović, Milan AU - Aleksić, Aleksandar AU - Radovanović, Radovan AU - Stojanović, Vladica AU - Čabarkapa, Milan AU - Ranđelović, Dragan PY - 2022 UR - https://jakov.kpu.edu.rs/handle/123456789/1633 AB - 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. PB - Basel : MDPI T2 - Mathematics T1 - One Aggregated Approach in Multidisciplinary Based Modeling to Predict Further Students’ Education VL - 10 IS - 14 SP - 2381 DO - 10.3390/math10142381 ER -
@article{ author = "Ranđelović, Milan and Aleksić, Aleksandar and Radovanović, Radovan and Stojanović, Vladica and Čabarkapa, Milan and Ranđelović, Dragan", year = "2022", 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.", publisher = "Basel : MDPI", journal = "Mathematics", title = "One Aggregated Approach in Multidisciplinary Based Modeling to Predict Further Students’ Education", volume = "10", number = "14", pages = "2381", doi = "10.3390/math10142381" }
Ranđelović, M., Aleksić, A., Radovanović, R., Stojanović, V., Čabarkapa, M.,& Ranđelović, D.. (2022). One Aggregated Approach in Multidisciplinary Based Modeling to Predict Further Students’ Education. in Mathematics Basel : MDPI., 10(14), 2381. https://doi.org/10.3390/math10142381
Ranđelović M, Aleksić A, Radovanović R, Stojanović V, Čabarkapa M, Ranđelović D. One Aggregated Approach in Multidisciplinary Based Modeling to Predict Further Students’ Education. in Mathematics. 2022;10(14):2381. doi:10.3390/math10142381 .
Ranđelović, Milan, Aleksić, Aleksandar, Radovanović, Radovan, Stojanović, Vladica, Čabarkapa, Milan, Ranđelović, Dragan, "One Aggregated Approach in Multidisciplinary Based Modeling to Predict Further Students’ Education" in Mathematics, 10, no. 14 (2022):2381, https://doi.org/10.3390/math10142381 . .