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A Survey on Clustering and Feature Selection Algorithm for Quickly Predicting Engineering Students

Year: 2018

Type: article

Abstract: Data mining(DM) is the process of extracting hidden and useful information in large data repositories. Knowledge Discovery in large data repositories is time consuming hence the need for fast algorithms for extracting useful knowledge from large database. This knowledge can be used to increase the quality of education. Educational Data Mining(EDM) is concerned with developing new methods to discover knowledge from educational/academic database and can be used for decision making in educational/academic systems. In our survey paper we would like to focus and analyze the various Data clustering and feature selection algorithms to bring the clarity in students' results and faculties contribution to make this one as success.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.21594168

Authors: H, Susheelamma K, H, Dr. Brahmananda S

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W7171284495

FWCI:

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