Evidential likelihood flatness as a way tomeasure data quality: the multinomial case

DOI

10.2991/ifsa-eusflat-15.2015.46How to use a DOI?

Keywords

Data quality, evidential likelihood, consonant mass function, non-specificity

Abstract

Likelihood functions, as well as the more recent concept of evidential likelihood, are essential statistical tools to perform estimation. Beyond the maximal likelihood value, the shape of the likelihood can also give interesting information about the data used to get the estimation. Indeed, it is generally acknowledged that more uncertain and scarce data will lead to flatter likelihoods. However, different aspects can affect this shape, and it may be worthwhile to separate various influences. In this paper, we discuss these influences and propose some practical ways to separate them into different measures. We demonstrate our approach on the particular case of the multinomial likelihood, which plays an important role in applications such as classification.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Liyao Ma
AU  - Sébastien Destercke
AU  - Yong Wang
PY  - 2015/06
DA  - 2015/06
TI  - Evidential likelihood flatness as a way tomeasure data quality: the multinomial case
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 313
EP  - 319
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.46
DO  - 10.2991/ifsa-eusflat-15.2015.46
ID  - Ma2015/06
ER  -