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» Online feature selection and classification
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ICANN
2005
Springer
14 years 1 months ago
A Neural Network Model for Inter-problem Adaptive Online Time Allocation
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
Matteo Gagliolo, Jürgen Schmidhuber
ICNC
2005
Springer
14 years 1 months ago
Support Vector Based Prototype Selection Method for Nearest Neighbor Rules
The Support vector machines derive the class decision hyper planes from a few, selected prototypes, the support vectors (SVs) according to the principle of structure risk minimizat...
Yuangui Li, Zhonghui Hu, Yunze Cai, Weidong Zhang
JIB
2007
172views more  JIB 2007»
13 years 7 months ago
The ABC (Analysing Biomolecular Contacts)-database
As protein-protein interactions are one of the basic mechanisms in most cellular processes, it is desirable to understand the molecular details of protein-protein contacts and ult...
Peter Walter, Sam Ansari, Volkhard Helms
BMCBI
2007
153views more  BMCBI 2007»
13 years 7 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
TEC
2008
146views more  TEC 2008»
13 years 7 months ago
An Evolutionary Algorithm Approach to Optimal Ensemble Classifiers for DNA Microarray Data Analysis
In general, the analysis of microarray data requires two steps: feature selection and classification. From a variety of feature selection methods and classifiers, it is difficult t...
Kyung-Joong Kim, Sung-Bae Cho