Educational Data Mining A Blend of Heuristic and K-Means Algorithm to Cluster Students to Predict Placement Chance IJTSRD


Educational data mining emphasizes on developing algorithms and new tools for identifying distinctive sorts of data that come from educational settings, to better understand students. The objective of this paper is to cluster efficient students among the students of the educational institution to predict placement chance. Data mining approach used is clustering. Ablend of heuristic and K-means algorithm is employed to cluster students based on KSA knowledge, Communication skill and attitude . To assess the performance of the program, a student data set from an institution in Bangalore were collected for the study as a synthetic knowledge. A model is proposed to obtain the result. The accuracy of the results obtained from the proposed algorithm was found to be promising when compared to other clustering algorithms.

Ashok. M. V | G. Hareesh Kumar “Educational Data Mining: A Blend of Heuristic and K-Means Algorithm to Cluster Students to Predict Placement Chance”

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018,

URL: http://www.ijtsrd.com/papers/ijtsrd18882.pdf

Paper URL: http://www.ijtsrd.com/computer-science/data-miining/18882/educational-data-mining-a-blend-of-heuristic-and-k-means-algorithm-to-cluster-students-to-predict-placement-chance/ashok-m-v

call for paper Computer Security, international journal Parallel Computing, science journal




Educational Data Mining A Blend of Heuristic and K-Means Algorithm to Cluster Students to Predict Placement Chance IJTSRD IEEE PAPER





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