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KDD
2003
ACM
180views Data Mining» more  KDD 2003»
16 years 6 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han
KES
2007
Springer
16 years 16 days ago
Inductive Concept Retrieval and Query Answering with Semantic Knowledge Bases Through Kernel Methods
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...
Nicola Fanizzi, Claudia d'Amato
CIKM
2008
Springer
15 years 8 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 6 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
BMCBI
2007
237views more  BMCBI 2007»
15 years 6 months ago
FLAME, a novel fuzzy clustering method for the analysis of DNA microarray data
Background: Data clustering analysis has been extensively applied to extract information from gene expression profiles obtained with DNA microarrays. To this aim, existing cluster...
Limin Fu, Enzo Medico