Document - Self-optimizing classifiers: formalization and design pattern

2008

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Self-optimizing classifiers: formalization and design pattern

Dazzi P., Pasquali M., Baraglia R., Panciatici A.

Classification Self-optimizing

In this paper we propose a design pattern for self-optimizing classification systems, i.e. classifiers able to adapt their behavior to the system changes. First, we provide a formalization of a self-optimizing classifier we use to derive the design pattern. Then, we describe the pattern classes, their interactions, and validate our approach applying the proposed pattern to a real scenario. Finally, to evaluate the proposed solution we compare the behavior of the self-optimizing classifier with a not self-optimizing one. Experimental results demonstrate the approach effectiveness.

Source: From Grids to Service and Pervasive Computing, edited by Thierry Priol, Marco Vanneschi, pp. 175–187. New York: Springer, 2008

Publisher: Springer, New York, USA

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BibTeX entry

@inbook{oai:it.cnr:prodotti:139033,
	title = {Self-optimizing classifiers: formalization and design pattern},
	author = {Dazzi P. and Pasquali M. and Baraglia R. and Panciatici A.},
	publisher = {Springer, New York, USA},
	doi = {10.1007/978-0-387-09455-7_13},
	booktitle = {From Grids to Service and Pervasive Computing, edited by Thierry Priol, Marco Vanneschi, pp. 175–187. New York: Springer, 2008},
	year = {2008}
}