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CSB
2005
IEEE
115views Bioinformatics» more  CSB 2005»
15 years 3 months ago
A New Clustering Strategy with Stochastic Merging and Removing Based on Kernel Functions
With hierarchical clustering methods, divisions or fusions, once made, are irrevocable. As a result, when two elements in a bottom-up algorithm are assigned to one cluster, they c...
Huimin Geng, Hesham H. Ali
70
Voted
CEC
2003
IEEE
15 years 2 months ago
Learning DFA: evolution versus evidence driven state merging
Learning Deterministic Finite Automata (DFA) is a hard task that has been much studied within machine learning and evolutionary computation research. This paper presents a new met...
Simon M. Lucas, T. Jeff Reynolds
ECAIW
2008
Springer
14 years 11 months ago
An Autonomous Algorithm for Generating and Merging Clinical Algorithms
Abstract. Procedural knowledge in medicine uses to come expressed as isolated sentences in Clinical Practice Guidelines (CPG) that describe how to act in front of specific health-c...
Francis Real, David Riaño
105
Voted
KR
2004
Springer
15 years 2 months ago
A Split-Combination Method for Merging Inconsistent Possibilistic Knowledge Bases
In this paper, a new method for merging multiple inconsistent knowledge bases in the framework of possibilistic logic is presented. We divide the fusion process into two steps: on...
Guilin Qi, Weiru Liu, David H. Glass
BMCBI
2010
164views more  BMCBI 2010»
14 years 6 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...