A fully sensitive correlation measure for data mining (2008)
- Authors:
- Autor USP: CAMPELLO, RICARDO JOSÉ GABRIELLI BARRETO - ICMC
- Unidade: ICMC
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Source:
- Título do periódico: Wit Transactions on Information and Communication Technologies
- ISSN: 1746-4463
- Volume/Número/Paginação/Ano: v. 20, p. 35-41, 2008
- Conference titles: International Conference on Data Mining, Protection, Detection, and Security Technologies
-
ABNT
CAMPELLO, Ricardo José Gabrielli Barreto; HRUSCHKA, Eduardo Raul. A fully sensitive correlation measure for data mining. Wit Transactions on Information and Communication Technologies[S.l: s.n.], 2008. -
APA
Campello, R. J. G. B., & Hruschka, E. R. (2008). A fully sensitive correlation measure for data mining. Wit Transactions on Information and Communication Technologies. -
NLM
Campello RJGB, Hruschka ER. A fully sensitive correlation measure for data mining. Wit Transactions on Information and Communication Technologies. 2008 ; 20 35-41. -
Vancouver
Campello RJGB, Hruschka ER. A fully sensitive correlation measure for data mining. Wit Transactions on Information and Communication Technologies. 2008 ; 20 35-41. - A robust methodology for comparing performances of clustering validity criteria
- Robust expansion of uncertain Volterra kernels into orthonormal series
- An introduction to models based on Laguerre, Kautz and other related orthonormal functions - part I: linear and uncertain models
- Density-based clustering validation
- A systematic comparative evaluation of biclustering techniques
- Comparison of distributed evolutionary k-means clustering algorithms
- On the evaluation of outlier detection and one-class classification methods
- Similarity measures for comparing biclusterings
- Relative validity criteria for community mining algorithms
- Fuzzy clustering algorithms and validity indices for distributed data
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