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TCBB
2011
13 years 2 months ago
Ensemble Learning with Active Example Selection for Imbalanced Biomedical Data Classification
—In biomedical data, the imbalanced data problem occurs frequently and causes poor prediction performance for minority classes. It is because the trained classifiers are mostly d...
Sangyoon Oh, Min Su Lee, Byoung-Tak Zhang
ICDM
2008
IEEE
112views Data Mining» more  ICDM 2008»
14 years 1 months ago
Supervised Inductive Learning with Lotka-Volterra Derived Models
We present a classification algorithm built on our adaptation of the Generalized Lotka-Volterra model, well-known in mathematical ecology. The training algorithm itself consists ...
Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar
VVS
1996
IEEE
98views Visualization» more  VVS 1996»
13 years 11 months ago
Classification and Local Error Estimation of Interpolation and Derivative Filters for Volume Rendering
We describe a new method for analyzing, classifying, and evaluating filters, which can be applied to interpolation filters, and derivative filters. Our analysis is based on the Ta...
Torsten Möller, Raghu Machiraju, Klaus Muelle...
BMCBI
2005
167views more  BMCBI 2005»
13 years 7 months ago
Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes
Background: The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer...
Patrick Warnat, Roland Eils, Benedikt Brors
BMCBI
2007
157views more  BMCBI 2007»
13 years 7 months ago
Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory
Background: Large-scale sequencing of entire genomes has ushered in a new age in biology. One of the next grand challenges is to dissect the cellular networks consisting of many i...
Feng Luo, Yunfeng Yang, Jianxin Zhong, Haichun Gao...