Comparison of methods for automated feature selection using a Self-Organising Map

Aliyu Usman Ahmad; Andrew Starkey

doi:10.1007/978-3-319-44188-7_10

Comparison of methods for automated feature selection using a Self-Organising Map

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

Abstract

The effective modelling of high-dimensional data with hundreds to thousands of features remains a challenging task in the field of machine learning. One of the key challenges is the implementation of effective methods for selecting a set of relevant features, which are buried in high-dimensional data along with irrelevant noisy features by choosing a subset of the complete set of input features that predicts the output with higher accuracy comparable to the performance of the complete input set. Kohonen’s Self Organising Neural Network MAP has been utilized in various ways for this task. In this work, a review of the appropriate application of multiple methods for this task is carried out. The feature selection approach based on analysis of the Self Organising network result after training is presented with comparison of performance of two methods.

Original language	English
Title of host publication	Engineering Applications of Neural Networks
Subtitle of host publication	17th International Conference, EANN 2016, Aberdeen, UK, September 2-5, 2016, Proceedings
Editors	Chrisina Jayne, Lazaros Iliadis
Publisher	Springer-Verlag
Pages	134-146
Number of pages	13
Volume	CCIS 269
ISBN (Electronic)	978-3-319-44188-7
ISBN (Print)	978-3-319-44187-0
DOIs	https://doi.org/10.1007/978-3-319-44188-7_10
Publication status	Published - 2016

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	629
ISSN (Print)	1865-0929

Keywords

Clustering
Self-organising neural network MAP
Feature selection
Engineering optimisation

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10.1007/978-3-319-44188-7_10Licence: Unspecified

Andrew Starkey
Person: Academic

Cite this

Ahmad, A. U., & Starkey, A. (2016). Comparison of methods for automated feature selection using a Self-Organising Map. In C. Jayne, & L. Iliadis (Eds.), Engineering Applications of Neural Networks: 17th International Conference, EANN 2016, Aberdeen, UK, September 2-5, 2016, Proceedings (Vol. CCIS 269, pp. 134-146). (Communications in Computer and Information Science; Vol. 629). Springer-Verlag. https://doi.org/10.1007/978-3-319-44188-7_10

Comparison of methods for automated feature selection using a Self-Organising Map. / Ahmad, Aliyu Usman; Starkey, Andrew.

Engineering Applications of Neural Networks: 17th International Conference, EANN 2016, Aberdeen, UK, September 2-5, 2016, Proceedings. ed. / Chrisina Jayne; Lazaros Iliadis. Vol. CCIS 269 Springer-Verlag, 2016. p. 134-146 (Communications in Computer and Information Science; Vol. 629).

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

Ahmad, AU & Starkey, A 2016, Comparison of methods for automated feature selection using a Self-Organising Map. in C Jayne & L Iliadis (eds), Engineering Applications of Neural Networks: 17th International Conference, EANN 2016, Aberdeen, UK, September 2-5, 2016, Proceedings. vol. CCIS 269, Communications in Computer and Information Science, vol. 629, Springer-Verlag, pp. 134-146. https://doi.org/10.1007/978-3-319-44188-7_10

Ahmad AU, Starkey A. Comparison of methods for automated feature selection using a Self-Organising Map. In Jayne C, Iliadis L, editors, Engineering Applications of Neural Networks: 17th International Conference, EANN 2016, Aberdeen, UK, September 2-5, 2016, Proceedings. Vol. CCIS 269. Springer-Verlag. 2016. p. 134-146. (Communications in Computer and Information Science). Epub 2016 Aug 19. doi: 10.1007/978-3-319-44188-7_10

Ahmad, Aliyu Usman ; Starkey, Andrew. / Comparison of methods for automated feature selection using a Self-Organising Map. Engineering Applications of Neural Networks: 17th International Conference, EANN 2016, Aberdeen, UK, September 2-5, 2016, Proceedings. editor / Chrisina Jayne ; Lazaros Iliadis. Vol. CCIS 269 Springer-Verlag, 2016. pp. 134-146 (Communications in Computer and Information Science).

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Comparison of methods for automated feature selection using a Self-Organising Map

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