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ESANN
2000
13 years 6 months ago
Bootstrapping Self-Organizing Maps to assess the statistical significance of local proximity
One of the attractive feature of Self-Organizing Maps (SOM) is the so-called "topological preservation property": observations that are close to each other in the input s...
Eric de Bodt, Marie Cottrell
CORR
2007
Springer
94views Education» more  CORR 2007»
13 years 4 months ago
Statistical tools to assess the reliability of self-organizing maps
Results of neural network learning are always subject to some variability, due to the sensitivity to initial conditions, to convergence to local minima, and, sometimes more dramat...
Eric de Bodt, Marie Cottrell, Michel Verleysen
IJCNN
2000
IEEE
13 years 9 months ago
EM Algorithms for Self-Organizing Maps
eresting web-available abstracts and papers on clustering: An Analysis of Recent Work on Clustering Algorithms (1999), Daniel Fasulo : This paper describes four recent papers on cl...
Tom Heskes, Jan-Joost Spanjers, Wim Wiegerinck
IJIT
2004
13 years 6 months ago
AudioMine: Medical Data Mining in Heterogeneous Audiology Records
We report on the results of a pilot study in which a data-mining tool was developed for mining audiology records. The records were heterogeneous in that they contained numeric, cat...
Shaun Cox, Michael P. Oakes, Stefan Wermter, Mauri...
IJON
2002
84views more  IJON 2002»
13 years 4 months ago
On the generative probability density model in the self-organizing map
The Self-Organizing Map, SOM, is a widely used tool in exploratory data analysis. A major drawback of the SOM has been the lack of a theoretically justified criterion for model se...
Timo Kostiainen, Jouko Lampinen