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» Ensemble Approach for the Classification of Imbalanced Data
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ICML
2007
IEEE
14 years 8 months ago
On learning with dissimilarity functions
We study the problem of learning a classification task in which only a dissimilarity function of the objects is accessible. That is, data are not represented by feature vectors bu...
Liwei Wang, Cheng Yang, Jufu Feng
WWW
2007
ACM
14 years 8 months ago
Extraction and search of chemical formulae in text documents on the web
Often scientists seek to search for articles on the Web related to a particular chemical. When a scientist searches for a chemical formula using a search engine today, she gets ar...
Bingjun Sun, Qingzhao Tan, Prasenjit Mitra, C. Lee...
KDD
2003
ACM
129views Data Mining» more  KDD 2003»
14 years 7 months ago
Empirical comparisons of various voting methods in bagging
Finding effective methods for developing an ensemble of models has been an active research area of large-scale data mining in recent years. Models learned from data are often subj...
Kelvin T. Leung, Douglas Stott Parker Jr.
BMCBI
2010
160views more  BMCBI 2010»
13 years 7 months ago
Annotation of gene promoters by integrative data-mining of ChIP-seq Pol-II enrichment data
Background: Use of alternative gene promoters that drive widespread cell-type, tissue-type or developmental gene regulation in mammalian genomes is a common phenomenon. Chromatin ...
Ravi Gupta, Priyankara Wikramasinghe, Anirban Bhat...
TNN
2010
176views Management» more  TNN 2010»
13 years 2 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao