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robertogreco : self-organizingmaps   3

Sugar Labs/SOM - Sugar Labs
"Self Organising Maps (SOMs) can act as 2d spatial summariser visualisations of multidimensional data. In the maps shown here, text distance metrics are generated from the weekly/monthly content on some of the more active mailing lists. Using a geographic like landscape metaphor, the height (colour gradient) indicates features with strong associations to all other features; proximity represents association between specific features (e.g. related terms), and label size indicates guide to basic frequency of a feature. There are many "correct" 2d map layouts for the same set of data (due to the multidimensional nature of the data), each map generation will usually settle into a slightly different set of local minima, but the associations are no less valid for each. After removing linguistic junk words, and word stemming, the maps currently pick the weeks/months top ~200 features by frequency."
maps  data  sugarlabs  som  self-organizingmaps  mapping 
june 2010 by robertogreco
OLPC research - OLPC
"This page provides links to research reports related to the OLPC project. See also Experience, Constructionism, Reviews of OLPC, and Class Acts (a FLOSS Manuals community publication) for articles and other anecdotal evidence."
education  evaluation  olpc  research  constructivism  experience  planceibal  som  self-organizingmaps  maps  mapping 
june 2010 by robertogreco
Self-organizing map - Wikipedia
"A self-organizing map (SOM) or self-organizing feature map (SOFM) is a type of artificial neural network that is trained using unsupervised learning to produce a low-dimensional (typically two-dimensional), discretized representation of the input space of the training samples, called a map. Self-organizing maps are different from other artificial neural networks in the sense that they use a neighborhood function to preserve the topological properties of the input space."
maps  mathematics  networks  optimization  datamining  database  clustering  classification  algorithms  ai  learning  programming  research  statistics  visualization  neuralnetworks  mapping  som  self-organizingmaps 
june 2010 by robertogreco

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