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@article{151846,
        author = {Abishake J and Roshan Kumar J and Abishek Js},
        title = {STUDENTS AND STAFFS PERFORMANCE PREDICTION USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {976-981},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151846},
        abstract = {In recent years, educational data mining (EDM) has become a new research field due to the development of various statistical methods to study data in the educational context. One such application is the early prediction of student performance. Weak disciples" in order to arrange some form of correction for them. . Since the number of attributes is large enough, a feature selection algorithm is applied to the data set to reduce the number of features. Then five types of machine learning algorithms (MLA) were applied to the data set, and it was found that the decision tree algorithm class gave the best results. Students and staffs performance prediction is very important to know a student progress rate. during this Research, we are attempting to seek out out student' current status, previous status and predict his/her future results. once the outcome, lecturers can provide him/her correct recommendation to avoid the poor result and can also groom the student. a lecturer can't monitor each and every single student at once. If a system can facilitate a lecturer regarding the scholars like that student needs which sort of help. The aim helps the student to avoid his/her predicted poor result and to improve their extra info activities based on the student’s performance level using Artificial Intelligence. This research would be useful for the students and staffs.},
        keywords = { Student Performance, Algorithm, Machine Learning, Education, Prediction, Data Mining},
        month = {},
        }