| Full text | |
| Author(s): |
Costa, Kelton A. P.
[1]
;
Pereira, Luis A. M.
[2]
;
Nakamura, Rodrigo Y. M.
[1]
;
Pereira, Clayton R.
[3]
;
Papa, Joao P.
[1]
;
Falcao, Alexandre Xavier
[2]
Total Authors: 6
|
| Affiliation: | [1] Univ Estadual Paulista, Dept Comp, Bauru - Brazil
[2] Univ Estadual Campinas, Inst Comp, Campinas - Brazil
[3] Univ Fed Sao Carlos, Dept Comp, BR-13560 Sao Carlos, SP - Brazil
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | INFORMATION SCIENCES; v. 294, p. 95-108, FEB 10 2015. |
| Web of Science Citations: | 28 |
| Abstract | |
We propose a nature-inspired approach to estimate the probability density function (pdf) used for data clustering based on the optimum-path forest algorithm (OPFC). OPFC interprets a dataset as a graph, whose nodes are the samples and each sample is connected to its k-nearest neighbors in a given feature space (a k-nn graph). The nodes of the graph are weighted by their pdf values and the pdf is computed based on the distances between the samples and their k-nearest neighbors. Once the k-nn graph is defined, OPFC finds one sample (root) at each maximum of the pdf and propagates one optimum-path tree (cluster) from each root to the remaining samples of its dome. Clustering effectiveness will depend on the pdf estimation, and the proposed approach efficiently computes the best value of k for a given application. We validate our approach in the context of intrusion detection in computer networks. First, we compare OPFC with data clustering based on k-means, and self-organization maps. Second, we evaluate several metaheuristic techniques to find the best value of k. (C) 2014 Elsevier Inc. All rights reserved. (AU) | |
| FAPESP's process: | 10/02045-3 - Intrusion Detection Based on Optimum-Path Forest |
| Grantee: | Clayton Reginaldo Pereira |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 11/14094-1 - Exploring Multi-labeling Approaches by Optimum-Path Forest |
| Grantee: | Luis Augusto Martins Pereira |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 09/16206-1 - New trends on optimum-path forest-based pattern recognition |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Research Grants - Young Investigators Grants |
| FAPESP's process: | 11/14058-5 - Exploring Sequential Learning Approaches for Optimum-Path Forest |
| Grantee: | Rodrigo Yuji Mizobe Nakamura |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 13/20387-7 - Hyperparameter optimization in deep learning arquitectures |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Scholarships abroad - Research |