Publication details
Conference Paper (international conference)
Simultaneous Visualization of Samples, Features and Multi-Labels
, , ,
: Proceedings of the 23rd International Conference on Pattern Recognition (ICPR), p. 3592-3597
: 23rd International Conference on Pattern Recognition ICPR 2016, (Cancún, MX, 20161204)
: 15H02719, JSPS KAKENHI
: Visualization, matrix factorization
: http://library.utia.cas.cz/separaty/2016/RO/haindl-0467543.pdf
(eng): Visualization helps us to understand single-label and multi-label classification problems. In this paper, we show several standard techniques for simultaneous visualization of samples, features and multi-classes on the basis of linear regression and matrix factorization. The experiment with two real-life multilabel datasets showed that such techniques are effective to know how labels are correlated to each other and how features are related to labels in a given multi-label classification problem.
: BD