Full text
|
PDF
- Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview |
Classification in sparse, high dimensional environments applied to distributed systems failure prediction
Citation
Navarro González, José Manuel and Parada Gélvez, Hugo Alexer and Dueñas López, Juan Carlos (2015). Classification in sparse, high dimensional environments applied to distributed systems failure prediction. In: "14th International Conference (ICAISC 2015)", 14/06/2015 - 19/06/2018, Zakopane, Poland. pp. 714-726. https://doi.org/10.1007/978-3-319-19369-4_63.
Description
| Title: | Classification in sparse, high dimensional environments applied to distributed systems failure prediction |
|---|---|
| Author/s: |
|
| Item Type: | Presentation at Congress or Conference (Article) |
| Event Title: | 14th International Conference (ICAISC 2015) |
| Event Dates: | 14/06/2015 - 19/06/2018 |
| Event Location: | Zakopane, Poland |
| Title of Book: | Artificial Intelligence and Soft Computing |
| Date: | 2015 |
| Subjects: | |
| Freetext Keywords: | Online failure prediction, Machine learning, System management, Automatic feature selection, Logistic regression, Multivariate prediction |
| Faculty: | E.T.S.I. Telecomunicación (UPM) |
| Department: | Ingeniería de Sistemas Telemáticos [hasta 2014] |
| Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
Abstract
Network failures are still one of the main causes of distributed systems’ lack of reliability. To overcome this problem we present an improvement over a failure prediction system, based on Elastic Net Logistic Regression and the application of rare events prediction techniques, able to work with sparse, high dimensional datasets. Specifically, we prove its stability, fine tune its hyperparameter and improve its industrial utility by showing that, with a slight change in dataset creation, it can also predict the location of a failure, a key asset when trying to take a proactive approach to failure management.
More information
| Item ID: | 41934 |
|---|---|
| DC Identifier: | http://oa.upm.es/41934/ |
| OAI Identifier: | oai:oa.upm.es:41934 |
| DOI: | 10.1007/978-3-319-19369-4_63 |
| Deposited by: | Memoria Investigacion |
| Deposited on: | 30 Jul 2016 08:49 |
| Last Modified: | 30 Jul 2016 08:49 |
