{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T17:05:26Z","timestamp":1778346326045,"version":"3.51.4"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031659959","type":"print"},{"value":"9783031659966","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-65996-6_19","type":"book-chapter","created":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T17:02:07Z","timestamp":1721926927000},"page":"219-227","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Comparative Analysis of Classical Machine Learning Techniques for Predicting Students\u2019 Exam Performance"],"prefix":"10.1007","author":[{"given":"Said A.","family":"Salloum","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ayham","family":"Salloum","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Khaled","family":"Shaalan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raghad","family":"Alfaisal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Azza","family":"Basiouni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,26]]},"reference":[{"key":"19_CR1","doi-asserted-by":"publisher","unstructured":"Alsharhan, A.M., Salloum, S. (2022). Precision education approaches to education data mining and analytics: a review. In: Hassanien, A.E., Rizk, R.Y., Sn\u00e1\u0161el, V., Abdel-Kader, R.F. (eds) The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022). AMLTA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 113, pp 337\u2013356. Springer, Cham (2022).https:\/\/doi.org\/10.1007\/978-3-031-03918-8_30","DOI":"10.1007\/978-3-031-03918-8_30"},{"key":"19_CR2","doi-asserted-by":"publisher","unstructured":"Salloum, S.A., Alshurideh, M., Elnagar, A., Shaalan, K. (2020). Mining in educational data: review and future directions. In: Hassanien, AE., Azar, A., Gaber, T., Oliva, D., Tolba, F. (eds) Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020). AICV 2020. Advances in Intelligent Systems and Computing, vol 1153, pp 92\u2013102. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-44289-7_9","DOI":"10.1007\/978-3-030-44289-7_9"},{"key":"19_CR3","doi-asserted-by":"crossref","unstructured":"Romero, C., Ventura, S.: Educational data mining: a review of the state of the art. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 40(6), 601\u2013618. (2010)","DOI":"10.1109\/TSMCC.2010.2053532"},{"key":"19_CR4","unstructured":"de Baker, R.S.J., Inventado, P.S.: Chapter 4: educational data mining and learning analytics. Comput. Sci. 7, 1\u201316 (2014)"},{"key":"19_CR5","unstructured":"Marsland, S.: Machine Learning: An Algorithmic Perspective, Chapman and Hall\/CRC, New York (2011)"},{"key":"19_CR6","series-title":"Studies in Systems, Decision and Control","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/978-3-030-47411-9_9","volume-title":"Recent Advances in Intelligent Systems and Smart Applications","author":"S Al Mansoori","year":"2021","unstructured":"Al Mansoori, S., Salloum, S.A., Shaalan, K.: The impact of artificial intelligence and information technologies on the efficiency of knowledge management at modern organizations: a systematic review. In: Al-Emran, M., Shaalan, K., Hassanien, A. (eds.) Recent Advances in Intelligent Systems and Smart Applications. SSDC, vol. 295, pp. 163\u2013182. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-47411-9_9"},{"key":"19_CR7","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"IH Witten","year":"2016","unstructured":"Witten, I.H., Frank, E., Hall, M., Pal, C.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, United States (2016)"},{"key":"19_CR8","first-page":"3","volume":"160","author":"SB Kotsiantis","year":"2007","unstructured":"Kotsiantis, S.B., Zaharakis, I., Pintelas, P.: Supervised machine learning: a review of classification techniques. Emerg. Artif. Intell. Appl. Comput. Eng. 160, 3\u201324 (2007)","journal-title":"Emerg. Artif. Intell. Appl. Comput. Eng."},{"key":"19_CR9","unstructured":"Lantz, B.: Machine Learning with R: Expert Techniques for Predictive Modeling, Packt Publishing Ltd (2019)"},{"key":"19_CR10","unstructured":"Students Performance in exams. In: Kaggle (2018). https:\/\/www.kaggle.com\/datasets\/spscientist\/students-performance-in-exams"},{"key":"19_CR11","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., Varoquaux, G., Gramfort, A., et al.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"19_CR12","first-page":"1157","volume":"3","author":"I Guyon","year":"2003","unstructured":"Guyon, I., Elisseeff, A.: An introduction to variable and feature selection. J. Mach. Learn. Res. 3, 1157\u20131182 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"19_CR13","doi-asserted-by":"publisher","DOI":"10.1002\/9781118548387","volume-title":"Applied Logistic Regression","author":"DW Jr Hosmer","year":"2013","unstructured":"Jr Hosmer, D.W., Lemeshow, S., Sturdivant, R.X.: Applied Logistic Regression. Wiley (2013)"},{"key":"19_CR14","doi-asserted-by":"publisher","DOI":"10.1201\/9781315139470","volume-title":"Classification and Regression Trees","author":"L Breiman","year":"2017","unstructured":"Breiman, L.: Classification and Regression Trees. Routledge (2017)"},{"key":"19_CR15","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45, 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"19_CR16","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/BF00994018","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20, 273\u2013297 (1995)","journal-title":"Mach. Learn."},{"key":"19_CR17","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"13","author":"T Cover","year":"1967","unstructured":"Cover, T., Hart, P.: Nearest neighbor pattern classification. IEEE Trans. Inf. theory 13, 21\u201327 (1967)","journal-title":"IEEE Trans. Inf. theory"},{"key":"19_CR18","unstructured":"Rish, I.: An empirical study of the naive Bayes classifier. In: IJCAI 2001 Workshop on Empirical Methods in Artificial Intelligence. Citeseer, pp 41\u201346 (2001)"},{"key":"19_CR19","unstructured":"Powers, D.M.W.: Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. arXiv Preprint arXiv:2010.16061 (2020)"},{"key":"19_CR20","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1016\/j.patrec.2005.10.010","volume":"27","author":"T Fawcett","year":"2006","unstructured":"Fawcett, T.: An introduction to ROC analysis. Pattern Recognit. Lett. 27, 861\u2013874 (2006)","journal-title":"Pattern Recognit. Lett."}],"container-title":["Communications in Computer and Information Science","Breaking Barriers with Generative Intelligence. Using GI to Improve Human Education and Well-Being"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-65996-6_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T17:09:58Z","timestamp":1721927398000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-65996-6_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031659959","9783031659966"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-65996-6_19","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"26 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BBGI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Breaking Barriers with Generative Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thessaloniki","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bbgi2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iis-international.org\/workshop1-program\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}