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ISCIS
2005
Springer
14 years 3 months ago
Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
Zeki Erdem, Robi Polikar, Nejat Yumusak, Fikret S....
CSDA
2008
126views more  CSDA 2008»
13 years 10 months ago
A new genetic algorithm in proteomics: Feature selection for SELDI-TOF data
Mass spectrometry from clinical specimens is used in order to identify biomarkers in a diagnosis. Thus, a reliable method for both feature selection and classification is required...
Christelle Reynès, Robert Sabatier, Nicolas...
KDD
2007
ACM
198views Data Mining» more  KDD 2007»
14 years 10 months ago
Applying Link-Based Classification to Label Blogs
In analyzing data from social and communication networks, we encounter the problem of classifying objects where there is an explicit link structure amongst the objects. We study t...
Smriti Bhagat, Graham Cormode, Irina Rozenbaum
MLDM
2009
Springer
14 years 4 months ago
PMCRI: A Parallel Modular Classification Rule Induction Framework
In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction...
Frederic T. Stahl, Max A. Bramer, Mo Adda
ICML
2006
IEEE
14 years 11 months ago
Feature subset selection bias for classification learning
Feature selection is often applied to highdimensional data prior to classification learning. Using the same training dataset in both selection and learning can result in socalled ...
Surendra K. Singhi, Huan Liu