Discovering knowledge rules with multi-objective evolutionary computing (2010)
- Authors:
- Autor USP: BATISTA, GUSTAVO ENRIQUE DE ALMEIDA PRADO ALVES - ICMC
- Unidade: ICMC
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Los Alamitos
- Date published: 2010
- ISBN: 9780769543000
- Source:
- Título: Proceedings
- Conference titles: International Conference on Machine Learning and Applications - ICMLA
-
ABNT
GIUSTI, Rafael e BATISTA, Gustavo Enrique de Almeida Prado Alves. Discovering knowledge rules with multi-objective evolutionary computing. 2010, Anais.. Los Alamitos: IEEE, 2010. Disponível em: http://ieeexplore.ieee.org/stamp/stamp.do?tp=&arnumber=5708822. Acesso em: 13 mar. 2026. -
APA
Giusti, R., & Batista, G. E. de A. P. A. (2010). Discovering knowledge rules with multi-objective evolutionary computing. In Proceedings. Los Alamitos: IEEE. Recuperado de http://ieeexplore.ieee.org/stamp/stamp.do?tp=&arnumber=5708822 -
NLM
Giusti R, Batista GE de APA. Discovering knowledge rules with multi-objective evolutionary computing [Internet]. Proceedings. 2010 ;[citado 2026 mar. 13 ] Available from: http://ieeexplore.ieee.org/stamp/stamp.do?tp=&arnumber=5708822 -
Vancouver
Giusti R, Batista GE de APA. Discovering knowledge rules with multi-objective evolutionary computing [Internet]. Proceedings. 2010 ;[citado 2026 mar. 13 ] Available from: http://ieeexplore.ieee.org/stamp/stamp.do?tp=&arnumber=5708822 - Time series classification with motifs and characteristics
- Uma avaliação sobre a identificação de Motifs em séries temporais
- A fuzzy classifier for data streams with infinitely delayed labels
- Fast unsupervised online drift detection using incremental Kolmogorov-Smirnov test
- A complexity-invariant measure based on fractal dimension for time series classification
- Towards automatic classification on flying insects using inexpensive sensors
- Data mining a trillion time series subsequences under dynamic time warping
- Distância invariante à complexidade baseada em dimensão fractal para classificação de séries temporais
- Unsupervised context switch for classification tasks on data streams with recurrent concepts
- On the need of class ratio insensitive drift tests for data streams
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