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» On learning algorithm selection for classification
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SIGKDD
2010
154views more  SIGKDD 2010»
13 years 3 months ago
A brief survey on sequence classification
Sequence classification has a broad range of applications such as genomic analysis, information retrieval, health informatics, finance, and abnormal detection. Different from the ...
Zhengzheng Xing, Jian Pei, Eamonn J. Keogh
ICPR
2006
IEEE
14 years 10 months ago
Boosted Band Ratio Feature Selection for Hyperspectral Image Classification
Band ratios have many useful applications in hyperspectral image analysis. While optimal ratios have been chosen empirically in previous research, we propose a principled algorith...
Antonio Robles-Kelly, Nianjun Liu, Terry Caelli, Z...
ICARIS
2009
Springer
14 years 20 days ago
Efficient Algorithms for String-Based Negative Selection
Abstract. String-based negative selection is an immune-inspired classification scheme: Given a self-set S of strings, generate a set D of detectors that do not match any element of...
Michael Elberfeld, Johannes Textor
BMCBI
2006
165views more  BMCBI 2006»
13 years 8 months ago
Improved variance estimation of classification performance via reduction of bias caused by small sample size
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
Ulrika Wickenberg-Bolin, Hanna Göransson, M&a...
TCSV
2008
195views more  TCSV 2008»
13 years 8 months ago
Locality Versus Globality: Query-Driven Localized Linear Models for Facial Image Computing
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...