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Review Paper On Student Performance Evaluation Through Supervised Learning Using Neural Network

Authors: Karan Manchandia*, Shweta Kondla, Vasudev Lambhate;

Review Paper On Student Performance Evaluation Through Supervised Learning Using Neural Network

Abstract

As we know that in maximum university the evaluation of the student’s performance I done manually by the faculties. This System of student performance evaluation is non-transparent and often leads to dissatisfaction among students. This project aims to solve the problem by designing a user interface which would work on supervised learning using Neural Network. 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.

Keywords

education, KDD, Neural Network, performance, evaluation.

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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