CLASSIFICATION DATA EXPLORATION METHODS IN MODERN REALTIME DATA WAREHOUSE

Authors

  • Jakub Chłapiński
  • Piotr Mazur
  • Jan Murlewski
  • Marek Kamiński
  • Bartosz Sakowicz

DOI:

https://doi.org/10.47839/ijc.7.1.483

Keywords:

Data Mining, Data warehouse, Classification method, Neural networks, Decision tree

Abstract

The goal of this article is to introduce problems that may arise during analysis of classification methods used in data mining applications. In the following sections some of the most common classification techniques are described along with several proposed extensions which allow these methods to be used in incremental data warehouses. The primary focus was aimed at the problem of performing incremental learning methods that may be used in near realtime data warehousing applications.

References

Burges C.J.C. A tutorial on support vector machines for pattern recognition, Data Mining and Knowledge Discovery 2(2).

Langey P., Iba W., Thompson K. “An analysis of Bayesian classifiers”, In Proc. of 10th National Conference on Artificial Intelligence, San Jose, CA, 1992, AAAI Press, – pp. 223-228.

L. Breiman, J. H. Friedman, A. Olshen, C. J. Stone. Classification and regression trees. Wadsworth, Belmont, CA, 1984.

Quinlan J.R. C4.5: Programs for machine learning. Morgan Kaufman, 1993.

Bigus J.P. Data mining with neutral networks, McGraw Hill, 1996.

S.E. Fahlman, C. Lebier, “The Cascade-Corelation Learning Architecture”, Technical Report CMU-CS-90-100, School of Computer Science, Carnegie Mellon University, August 1991.

Agrawal R., Srikant R. Fast Algorithms for Mining Association Rules, Proc. of 1994 International Conference on Very Large Databases VLDB, Santiago de Chile, September 12-15, Morgan Kaufman, 1994. –pp. 487-499.

Quinlan J.R. Induction of decision trees. Machine Learning 1(1), – pp.81-106.

Agrawal R., Imielinski T., Swami A. Mining association rules between sets of items in large databases, Proc. of 1993 ACM SIGMOD International Conference on Management of Data, Washington D.C., May 26-28, ACM Press 1993, – pp. 207-216.

Gupta, H.; Mumick, I.S. Selection of views to materialize in a data warehouse, IEEE Transactions Knowledge and Data Engineering, Volume 17, Issue 1, Jan 2005, – pp.24-43.

Downloads

Published

2014-08-01

How to Cite

Chłapiński, J., Mazur, P., Murlewski, J., Kamiński, M., & Sakowicz, B. (2014). CLASSIFICATION DATA EXPLORATION METHODS IN MODERN REALTIME DATA WAREHOUSE. International Journal of Computing, 7(1), 6-12. https://doi.org/10.47839/ijc.7.1.483

Issue

Section

Articles