Data Mining Model Based on Interval-valued Clustering

Volume 4 Issue 3 September - November 2016

Research Paper

Data Mining Model Based on Interval-valued Clustering

M. Bhargavi*

Assistant Professor, Department of Computer Science and Engineering, Sree Vidyanikethan Engineering College, Tirupati, India.

Bhargavi, M. (2016). Data Mining Model Based on Interval-Valued Clustering. i-manager’s Journal on Computer Science, 4(3), 1-10. https://doi.org/10.26634/jcom.4.3.8283

Abstract

Discovering potential patterns from complex data is a hot research topic. In this paper, the author proposes an iterative data mining model based on "Interval-Value" clustering, "Interval-Interval" clustering, and "Interval-Matrix" clustering. "Interval-Value" clustering uses the features of interval data and digital threshold and designed by "Netting"→ "Type-I clustering"→"Type-II clustering"; "Interval-Interval" clustering uses the features of interval data and interval threshold and designed with interval medium clustering; "Interval-Matrix" clustering uses the features of interval data and matrix threshold and designed by matrix threshold clustering. Motivation of the author is to mine the interval-valued association rules for giving dataset, and the experimental study is conducted to verify the new data mining method. Experimental results show that the data mining model based on interval-valued clustering is feasible and effective.