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IFIP12
2008
13 years 9 months ago
Bayesian Networks Optimization Based on Induction Learning Techniques
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Paola Britos, Pablo Felgaer, Ramón Garc&iac...
SIGKDD
2010
154views more  SIGKDD 2010»
13 years 2 months ago
A brief survey on sequence classification
Sequence classification has a broad range of applications such as genomic analysis, information retrieval, health informatics, finance, and abnormal detection. Different from the ...
Zhengzheng Xing, Jian Pei, Eamonn J. Keogh
ICML
2006
IEEE
14 years 8 months ago
Hierarchical classification: combining Bayes with SVM
We study hierarchical classification in the general case when an instance could belong to more than one class node in the underlying taxonomy. Experiments done in previous work sh...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
MICAI
2010
Springer
13 years 6 months ago
Supervised Machine Learning for Predicting the Meaning of Verb-Noun Combinations in Spanish
The meaning of such verb-noun combinations as take care, undertake work, pay attention can be generalized as DO what is designated by the noun. Likewise, the meaning of make a deci...
Olga Kolesnikova, Alexander F. Gelbukh
GECCO
2000
Springer
112views Optimization» more  GECCO 2000»
13 years 11 months ago
Linguistic Rule Extraction by Genetics-Based Machine Learning
This paper shows how linguistic classification knowledge can be extracted from numerical data for pattern classification problems with many continuous attributes by genetic algori...
Hisao Ishibuchi, Tomoharu Nakashima