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.
Original language | English |
---|---|
Title of host publication | ICPRAM 2015 - Proceedings of the International Conference on Pattern Recognition Applications and Methods, Volume 1, Lisbon, Portugal, 10-12 January, 2015 |
Editors | Maria De Marsico, Mario Figueiredo, Ana Fred |
Publisher | SciTePress |
Pages | 348-353 |
Number of pages | 6 |
Volume | 1 |
ISBN (Electronic) | 9789897580765 |
Publication status | Published - 2015 |
Externally published | Yes |
Event | 4th International Conference on Pattern Recognition Applications and Methods - Lisbon, Portugal Duration: 10 Jan 2015 → 12 Jan 2015 Conference number: 4th |
Publication series
Name | ICPRAM 2015 - 4th International Conference on Pattern Recognition Applications and Methods, Proceedings |
---|---|
Volume | 1 |
Conference
Conference | 4th International Conference on Pattern Recognition Applications and Methods |
---|---|
Abbreviated title | ICPRAM 2015 |
Country/Territory | Portugal |
City | Lisbon |
Period | 10/01/15 → 12/01/15 |
Keywords
- Data mining
- Differential evolution
- Distance metrics
- Fuzzy C-Means clustering
- Genetic algorithms
- Overfitting
- Particle swarm optimization
- Time series
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition