Dis-function: Learning distance functions interactively

IEEE VAST, pp. 83-92, 2012.

Cited by: 32|Bibtex|Views19|DOI:https://doi.org/10.1109/VAST.2012.6400486
EI
Other Links: dblp.uni-trier.de|dl.acm.org

Abstract:

The world's corpora of data grow in size and complexity every day, making it increasingly difficult for experts to make sense out of their data. Although machine learning offers algorithms for finding patterns in data automatically, they often require algorithm-specific parameters, such as an appropriate distance function, which are outsi...More

Code:

Data:

Full Text
Your rating :
0

 

Tags
Comments