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2015 | OriginalPaper | Buchkapitel

Binary Flower Pollination Algorithm and Its Application to Feature Selection

verfasst von : Douglas Rodrigues, Xin-She Yang, André Nunes de Souza, João Paulo Papa

Erschienen in: Recent Advances in Swarm Intelligence and Evolutionary Computation

Verlag: Springer International Publishing

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Abstract

The problem of feature selection has been paramount in the last years, since it can be as important as the classification step itself. The main goal of feature selection is to find out the subset of features that optimize some fitness function, often in terms of a classifier’s accuracy or even the computational burden for extracting each feature. Therefore, the approaches to feature selection can be modeled as optimization tasks. In this chapter, we evaluate a binary-constrained version of the Flower Pollination Algorithm (FPA) for feature selection, in which the search space is a boolean lattice where each possible solution, or a string of bits, denotes whether a feature will be used to compose the final set. Numerical experiments over some public and private datasets have been carried out and comparison with Particle Swarm Optimization, Harmony Search and Firefly Algorithm has demonstrated the suitability of the FPA for feature selection.

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Vorheriges Kapitel Hybrid Metaheuristic Algorithms: Past, Present, and Future

Nächstes Kapitel Bat Algorithm Application for the Single Row Facility Layout Problem

The first four datasets can be found on http://featureselection.asu.edu/datasets.php.

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Titel: Binary Flower Pollination Algorithm and Its Application to Feature Selection
verfasst von: Douglas Rodrigues
Xin-She Yang
André Nunes de Souza
João Paulo Papa
Verlag: Springer International Publishing
Buch: Recent Advances in Swarm Intelligence and Evolutionary Computation
Print ISBN: 978-3-319-13825-1

Electronic ISBN: 978-3-319-13826-8

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-13826-8_5

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