WEKA AS A DATA MINING TOOL TO ANALYZE STUDENTS' ACADEMIC PERFORMANCES USING NAÏVE BAYES CLASSIFIER- A SURVEY

In Indian Education System, the student performance evaluation is done by faculty manually. This System of student performance evaluation is non-transparent and often leads to dissatisfaction of student. This project aims to solve this problem by designing a user interface which would work on learning using Naïve Bayes Classifier.In evaluating the marks of students by faculty, many times there is partiality done by faculty while giving marks to the students. Therefore to cease this problem the concept of data mining is introduced.   

Data mining techniques are widely used in educational field to find new hidden patterns from student’s data. The hidden patterns that are discovered can be used to understand the problem arise in the educational field. Data Mining (DM), or Knowledge Discovery in Databases (KDD), is an approach to discover useful information from large amount of data. DM techniques apply various methods in order to discover and extract patterns from stored data. The pattern found will be used to solve a number of problems occurred in many fields such as education, economic, business, statistics, medicine, and sport. The large volume of data stored in those areas demands for DM approach because the resulting analysis is much more precise and accurate.