A NOVEL DATA CLEANING THROUGH MINIMUM SPANNING TREE FOR DATA MINING

[ 31 May 2020 | vol. 13 | no. 1 | pp. 31-36]

About Authors:

T. Karthikeyan1, S. John Peter2 and S.Chidambaranathan3
-1Department of Computer Science, PSG College of Arts and Science, Coimbatore, Tamil Nadu, India
-2Department of Computer Science and Research Center, St. Xavier’s College, Palayamkottai, Tamil Nadu, India
-3Department of MCA, St. Xavier’s College, Palayamkottai, Tamil Nadu, India

Abstract:

Detecting outliers in database (as unusual objects) using Minimum Spanning Tree is a big desire. It is an important task in wide variety of application areas. In this paper we propose a Minimum Spanning Tree based algorithm for detecting outliers. The outliers are detected from the data set based on degree number of an object (point) and distance between objects in the data set (MST).

Keywords:

Euclidean minimum spanning tree, Degree number, Outliers, nearest neighbor

 

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