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» Data selection for support vector machine classifiers
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ICML
2009
IEEE
15 years 4 months ago
Fast evolutionary maximum margin clustering
The maximum margin clustering approach is a recently proposed extension of the concept of support vector machines to the clustering problem. Briefly stated, it aims at finding a...
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer
BMCBI
2008
202views more  BMCBI 2008»
14 years 10 months ago
Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data
Background: Integrating data from multiple global assays and curated databases is essential to understand the spatiotemporal interactions within cells. Different experiments measu...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...
KES
2008
Springer
14 years 10 months ago
Classification and Retrieval through Semantic Kernels
Abstract. This work proposes a family of language-independent semantic kernel functions defined for individuals in an ontology. This allows exploiting wellfounded kernel methods fo...
Claudia d'Amato, Nicola Fanizzi, Floriana Esposito
ESANN
2004
14 years 11 months ago
Evolutionary tuning of multiple SVM parameters
The problem of model selection for support vector machines (SVMs) is considered. We propose an evolutionary approach to determine multiple SVM hyperparameters: The covariance matr...
Frauke Friedrichs, Christian Igel
CIKM
2000
Springer
15 years 2 months ago
Scalable association-based text classification
Naïve Bayes (NB) classifier has long been considered a core methodology in text classification mainly due to its simplicity and computational efficiency. There is an increasing n...
Dimitris Meretakis, Dimitris Fragoudis, Hongjun Lu...