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» Dimensionality Reduction for Classification
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KDD
2006
ACM
149views Data Mining» more  KDD 2006»
16 years 3 months ago
Regularized discriminant analysis for high dimensional, low sample size data
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
Jieping Ye, Tie Wang
AAAI
2006
15 years 4 months ago
A Direct Evolutionary Feature Extraction Algorithm for Classifying High Dimensional Data
Among various feature extraction algorithms, those based on genetic algorithms are promising owing to their potential parallelizability and possible applications in large scale an...
Qijun Zhao, David Zhang, Hongtao Lu
ICPR
2006
IEEE
16 years 4 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
JMLR
2010
101views more  JMLR 2010»
14 years 10 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
PAA
2008
15 years 3 months ago
Prototype reduction using an artificial immune model
Artificial immune system (AIS)-based pattern classification approach is relatively new in the field of pattern recognition. The study explores the potentiality of this paradigm in ...
Utpal Garain