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IJCNN
2006
IEEE
13 years 11 months ago
Pattern Selection for Support Vector Regression based on Sparseness and Variability
— Support Vector Machine has been well received in machine learning community with its theoretical as well as practical value. However, since its training time complexity is cubi...
Jiyoung Sun, Sungzoon Cho
ACSC
2005
IEEE
13 years 11 months ago
The Electronic Primaries: Predicting the U.S. Presidency Using Feature Selection with Safe Data Reduction
The data mining inspired problem of finding the critical, and most useful features to be used to classify a data set, and construct rules to predict the class of future examples ...
Pablo Moscato, Luke Mathieson, Alexandre Mendes, R...
GFKL
2005
Springer
105views Data Mining» more  GFKL 2005»
13 years 11 months ago
Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse
In classification, with an increasing number of variables, the required number of observations grows drastically. In this paper we present an approach to put into effect the maxi...
Gero Szepannek, Claus Weihs
PKDD
2001
Springer
127views Data Mining» more  PKDD 2001»
13 years 9 months ago
Sentence Filtering for Information Extraction in Genomics, a Classification Problem
In some domains, Information Extraction (IE) from texts requires syntactic and semantic parsing. This analysis is computationally expensive and IE is potentially noisy if it applie...
Claire Nedellec, Mohamed Ould Abdel Vetah, Philipp...
KDD
2004
ACM
302views Data Mining» more  KDD 2004»
14 years 5 months ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu