BibTeX
@MISC{Kaski_chapter12,
author = {Samuel Kaski and Janne Sinkkonen and Jaakko Peltonen},
title = {Chapter 12 Learning metrics},
year = {}
}
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Abstract
Visualization and clustering of multivariate data are usually based on mutual distances of samples, measured by heuristic means such as the Euclidean distance of vectors of extracted features. Our recently developed methods remove this arbitrariness by learning to measure important differences. The effect is equivalent to changing the metric of the
