Volume 7 Number 2 (Feb. 2012)
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JSW 2012 Vol.7(2): 479-484 ISSN: 1796-217X
doi: 10.4304/jsw.7.2.479-484

Information Decay in Building Predictive Models Using Temporal Data

Lasheng Yu and Mukwende Placide
Department of Computer Science ,Central South University, Changsha, China, 410083

Abstract—Most predictive data mining methods are based on the assumption that the historical data involved in building and verifying a model are the best estimator of what will happen in the future. However, the relevance of past to the future depends on the application domain in a specific timeframe. In this paper, we present a method of predicting the future from temporal data using information decay technique that estimate the relevance of the past to the future with the help of the knowledge of the information lifetime of the temporal data. We show how to use a decision tree data mining technique to build an information-decaybased predictive model by introducing an information decay method in impurity measure functions. The relevance of the concepts is proven by comparing two decision tree-based classifiers: one built using information decay over a specific timeframe and the other built setting aside the time factor.

Index Terms—Information decay, predictive model, data mining, classification, temporal data


Cite: Lasheng Yu and Mukwende Placide, "Information Decay in Building Predictive Models Using Temporal," Journal of Software vol. 7, no. 2, pp. 479-484, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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