An Extensible Data Mining and Pattern Recognition System

G. Sanchez-Diaz and A. Ramirez-Narvaez (Mexico)


Data mining, extensible system, Pattern Recognition and Logical Combinatorial Pattern Recognition.


Over the last decade, in Data mining and Pattern Recognition several algorithms have been integrated in software systems. There is a considerable quantity of software systems that integrate many algorithm and techniques. However, there is not a fixed set of algorithms that resolve all or many problems and applications, or any software system that allows an interaction between any two algorithms to solve a specific problem. In this paper, we propose a new extensible system that allows adding, removing and modifying algorithms, where the output of one algorithm can be the input of another algorithm. The extensible system proposed is focused in the Logical Combinatorial Pattern Recognition algorithms and data set formats.

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