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» Arguing from Experience to Classifying Noisy Data
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BMCBI
2008
114views more  BMCBI 2008»
13 years 8 months ago
A visual analytics approach for understanding biclustering results from microarray data
Background: Microarray analysis is an important area of bioinformatics. In the last few years, biclustering has become one of the most popular methods for classifying data from mi...
Rodrigo Santamaría, Roberto Therón, ...
IJCAI
1989
13 years 10 months ago
Noise-Tolerant Instance-Based Learning Algorithms
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
David W. Aha, Dennis F. Kibler
BMCBI
2006
173views more  BMCBI 2006»
13 years 8 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
ISMIS
2005
Springer
14 years 2 months ago
Scalable Inductive Learning on Partitioned Data
With the rapid advancement of information technology, scalability has become a necessity for learning algorithms to deal with large, real-world data repositories. In this paper, sc...
Qijun Chen, Xindong Wu, Xingquan Zhu
BMCBI
2008
106views more  BMCBI 2008»
13 years 8 months ago
Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spect
Background: Mass spectrometry for biological data analysis is an active field of research, providing an efficient way of high-throughput proteome screening. A popular variant of m...
Wouter Meuleman, Judith Y. M. N. Engwegen, Marie-C...