Preprocessing and Feature Extraction Process in Predicting Students Performance using Clustering Technique
K. Govindasamy1, T. Velmurugan2
1Mr. K. GOVINDASAMY, Research Scholar, Department of Computer Science, School of Computing Science, VISTAS, Chennai, Tamil Nadu, India.
2Dr. T. VELMURUGAN, PG and Research Department of Computer Science, D.G. Vaishanav College, Chennai, Tamil Nadu, India.

Manuscript received on 12 April 2019 | Revised Manuscript received on 18 May 2019 | Manuscript published on 30 May 2019 | PP: 2407-2413 | Volume-8 Issue-1, May 2019 | Retrieval Number: A1960058119/19©BEIESP
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Abstract: Analyzing students’ performance patterns using various statistical techniques always remain a critical task for many researches. This research paper focuses on basic preprocessing and extraction techniques followed before analyzing the student’s performance in academics. The collected information from various colleges has to be cleaning process for removing irrelevancy in data. The repeated records and unfilled data are removed in cleaning stage. The features are to be extracted from the preprocessed record. The research mainly concentrated on analyzing students’ performance from collected information. The extraction process implemented in this research work carefully examined in extracting the necessary features for analyzing process.
Index Terms: Educational Data Mining, Feature extraction, Clustering, E-Learning.

Scope of the Article: E-Learning