• Manpreet kaur
• Er.chamkaur singh

Educational Data Mining (EDM) is an emerging research area help the educational institutions to improve the performance of their students. Feature Selection (FS) algorithms remove irrelevant data from the educational dataset and hence increases the performance of classifiers used in EDM techniques. This paper present an analysis of the performance of feature selection algorithms on student data set. .In this papers the different problems that are defined in problem formulation. All these problems are resolved in future. Furthermore the paper is an attempt of playing a positive role in the improvement of education quality, as well as guides new researchers in making academic intervention. There are many techniques being anticipated to assess the student academic performance in way of making fruit full future of a student. Predicting performance of student has been continued to a hot topic in the Educational data mining domain. Data mining is considered to be one of the best choices for the researchers to analyse student’s performance. Feature Selection is very dynamic and productive field and research area of machine learning and data mining. The main goal of feature selection is to choose a subset by eliminating non-predictive data. Furthermore, it increases the predictive accuracy and reduces the complexity of learned results .The effectiveness of student performance prediction models can be increased in connection with feature selection techniques. In this paper 12960 instances are identified. In the future result is improved.

EDM, Data, mining, feature, accuracy etc

"EDUCATIONAL DATA MINING USING NURSARY DATASET WITH DIFFERENT TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.85-90, July-2018, Available :http://www.jetir.org/papers/JETIR1807016.pdf

"EDUCATIONAL DATA MINING USING NURSARY DATASET WITH DIFFERENT TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp85-90, July-2018, Available at : http://www.jetir.org/papers/JETIR1807016.pdf