Pattern-based Subspace Classification Approach

Citation:
Salama, M., A. E. Hassanien, and A. A. Fahmy, "Pattern-based Subspace Classification Approach", The Second IEEE World Congress on Nature and Biologically Inspired Computing (NaBIC2010), Kitakyushu- Japan, 15 Dec, 2010.

Date Presented:

15 Dec

Abstract:

The use of patterns in predictive models has received a lot of attention in recent years. This paper presents a pattern-based classification model which extracts the patterns that have similarity among all objects in a specific class. This introduced model handles the problem of the dependence on a user-defined threshold that appears in the pattern-based subspace clustering. The experimental results obtained, show that the overall pattern-based classification accuracy is high compared with other machine learning techniques including Support vector machine, Bayesian Network, multi-layer perception and decision trees.

Notes:

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