On the Application of Bio-Inspired Optimization Algorithms to Fuzzy C-Means Clustering of Time Series

Muhammad Marwan Muhammad Fuad

2015

Abstract

Fuzzy c-means clustering (FCM) is a clustering method which is based on the partial membership concept. As with the other clustering methods, FCM applies a distance to cluster the data. While the Euclidean distance is widely-used to perform the clustering task, other distances have been suggested in the literature. In this paper we study the use of a weighted combination of metrics in FCM clustering of time series where the weights in the combination are the outcome of an optimization process using differential evolution, genetic algorithms, and particle swarm optimization as optimizers. We show how the overfitting phenomenon interferes in the optimization process that the optimal results obtained during the training stage degrade during the testing stage as a result of overfitting.

Paper Citation

in Harvard Style

Muhammad Fuad M. (2015). On the Application of Bio-Inspired Optimization Algorithms to Fuzzy C-Means Clustering of Time Series . In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-076-5, pages 348-353. DOI: 10.5220/0005276203480353

in Bibtex Style

@conference{icpram15,
author={Muhammad Marwan Muhammad Fuad},
title={On the Application of Bio-Inspired Optimization Algorithms to Fuzzy C-Means Clustering of Time Series},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2015},
pages={348-353},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005276203480353},
isbn={978-989-758-076-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - On the Application of Bio-Inspired Optimization Algorithms to Fuzzy C-Means Clustering of Time Series
SN - 978-989-758-076-5
AU - Muhammad Fuad M.
PY - 2015
SP - 348
EP - 353
DO - 10.5220/0005276203480353