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» Anytime Exploratory Data Analysis for Massive Data Sets
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ESANN
2008
13 years 8 months ago
Parallelizing single patch pass clustering
Clustering algorithms such as k-means, the self-organizing map (SOM), or Neural Gas (NG) constitute popular tools for automated information analysis. Since data sets are becoming l...
Nikolai Alex, Barbara Hammer
MKM
2007
Springer
14 years 1 months ago
Using Formal Concept Analysis in Mathematical Discovery
Formal concept analysis (FCA) comprises a set of powerful algorithms which can be used for data analysis and manipulation, and a set of visualisation tools which enable the discove...
Simon Colton, Daniel Wagner
IGARSS
2010
13 years 5 months ago
Geospatiotemporal data mining in an early warning system for forest threats in the United States
We investigate the potential of geospatiotemporal data mining of multi-year land surface phenology data (250 m Normalized Difference Vegetation Index (NDVI) values derived from th...
Forrest M. Hoffman, Richard Tran Mills, Jitendra K...
DATAMINE
2006
139views more  DATAMINE 2006»
13 years 7 months ago
VizRank: Data Visualization Guided by Machine Learning
Data visualization plays a crucial role in identifying interesting patterns in exploratory data analysis. Its use is, however, made difficult by the large number of possible data p...
Gregor Leban, Blaz Zupan, Gaj Vidmar, Ivan Bratko
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