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TNN
1998
146views more  TNN 1998»
13 years 8 months ago
Fuzzy lattice neural network (FLNN): a hybrid model for learning
— This paper proposes two hierarchical schemes for learning, one for clustering and the other for classification problems. Both schemes can be implemented on a fuzzy lattice neu...
Vassilios Petridis, Vassilis G. Kaburlasos
BMCBI
2007
153views more  BMCBI 2007»
13 years 8 months ago
Analysis of nanopore detector measurements using Machine-Learning methods, with application to single-molecule kinetic analysis
Background: A nanopore detector has a nanometer-scale trans-membrane channel across which a potential difference is established, resulting in an ionic current through the channel ...
Matthew Landry, Stephen Winters-Hilt
BMCBI
2008
114views more  BMCBI 2008»
13 years 8 months ago
Combining classifiers for improved classification of proteins from sequence or structure
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
CSL
2010
Springer
13 years 8 months ago
Improving supervised learning for meeting summarization using sampling and regression
Meeting summarization provides a concise and informative summary for the lengthy meetings and is an effective tool for efficient information access. In this paper, we focus on ext...
Shasha Xie, Yang Liu
KDD
2009
ACM
142views Data Mining» more  KDD 2009»
14 years 9 months ago
Quantification and semi-supervised classification methods for handling changes in class distribution
In realistic settings the prevalence of a class may change after a classifier is induced and this will degrade the performance of the classifier. Further complicating this scenari...
Jack Chongjie Xue, Gary M. Weiss