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» Artificial Data Sets Based on Knowledge Generators: Analysis...
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KDD
2003
ACM
180views Data Mining» more  KDD 2003»
14 years 9 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
BMCBI
2006
142views more  BMCBI 2006»
13 years 8 months ago
Improving the Performance of SVM-RFE to Select Genes in Microarray Data
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
Yuanyuan Ding, Dawn Wilkins
BMCBI
2010
118views more  BMCBI 2010»
13 years 8 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
IEAAIE
2010
Springer
13 years 6 months ago
Using Remote Data Mining on LIDAR and Imagery Fusion Data to Develop Land Cover Maps
Remote sensing based on imagery has traditionally been the main tool used to extract land uses and land cover (LULC) maps. However, more powerful tools are needed in order to fulfi...
Jorge García-Gutiérrez, Francisco Ma...
WWW
2008
ACM
14 years 9 months ago
Learning to classify short and sparse text & web with hidden topics from large-scale data collections
This paper presents a general framework for building classifiers that deal with short and sparse text & Web segments by making the most of hidden topics discovered from larges...
Xuan Hieu Phan, Minh Le Nguyen, Susumu Horiguchi