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ICMLA
2008
13 years 8 months ago
Mapping Uncharted Waters: Exploratory Analysis, Visualization, and Clustering of Oceanographic Data
In this paper we describe an interdisciplinary collaboration between researchers in machine learning and oceanography. The collaboration was formed to study the problem of open oc...
Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinb...
BMCBI
2005
161views more  BMCBI 2005»
13 years 6 months ago
Non-linear mapping for exploratory data analysis in functional genomics
Background: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory...
Francisco Azuaje, Haiying Wang, Alban Chesneau
AUSDM
2007
Springer
101views Data Mining» more  AUSDM 2007»
13 years 11 months ago
Exploratory Multilevel Hot Spot Analysis: Australian Taxation Office Case Study
Population based real-life datasets often contain smaller clusters of unusual sub-populations. While these clusters, called `hot spots', are small and sparse, they are usuall...
Denny, Graham J. Williams, Peter Christen
ACSW
2004
13 years 8 months ago
Visualisation and Comparison of Image Collections based on Self-organised Maps
Self-organised maps (SOM) have been widely used for cluster analysis and visualisation purposes in exploratory data mining. In image retrieval applications, SOMs have been used to...
Da Deng, Jianhua Zhang, Martin K. Purvis
ADBIS
2007
Springer
145views Database» more  ADBIS 2007»
14 years 1 months ago
A Method for Comparing Self-organizing Maps: Case Studies of Banking and Linguistic Data
The method of self-organizing maps (SOM) is a method of exploratory data analysis used for clustering and projecting multi-dimensional data into a lower-dimensional space to reveal...
Toomas Kirt, Ene Vainik, Leo Vohandu