MultiResolution Complexity Analysis. A Novel Method for Partitioning Datasets into Regions of Different Classification Complexity

ARMANO, GIULIANO;TAMPONI, EMANUELE
2015-01-01

Abstract

Systems for complexity estimation typically aim to quantify the overall complexity of a domain, with the goal of comparing the hardness of different datasets or to associate a classification task to an algorithm that is deemed best suited for it. In this work we describe MultiResolution Complexity Analysis, a novel method for partitioning a dataset into regions of different classification complexity, with the aim of highlighting sources of complexity or noise inside the dataset. Initial experiments have been carried out on relevant datasets, proving the effectiveness of the proposed method.
2015
Inglese
ICPRAM 2015: Proceedings of the International Conference on Pattern Recognition Applications and Methods
978-989758076-5
1
334
341
8
4th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2015
Contributo
Esperti anonimi
January, 10-12, 2015
Lisbon, Portugal
internazionale
scientifica
no
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Armano, Giuliano; Tamponi, Emanuele
273
2
4.1 Contributo in Atti di convegno
reserved
info:eu-repo/semantics/conferencePaper
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