Depth-weighted Bayes classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F18%3A73587215" target="_blank" >RIV/61989592:15310/18:73587215 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0167947318300124" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0167947318300124</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.csda.2018.01.011" target="_blank" >10.1016/j.csda.2018.01.011</a>

Result language
angličtina
Original language name
Depth-weighted Bayes classification
Original language description
Two procedures for supervised classification are proposed. These are based on data depth and focus on the centre of each class. The classifiers add either a depth or a depth rank term to the objective function of the Bayes classifier. The cost of misclassifying a point depends not only on a class where it belongs, but also on its centrality with respect to this class. The classification of points that are more central is enforced while outliers are downweighted. The proposed objective function can also be used to evaluate the performance of other classifiers instead of the usual average misclassification rate. Use of the depth function increases robustness of the new procedures against the large inclusion of contaminated data that often impede the Bayes classifier. Properties of the new methods are investigated and compared with those of the Bayes classifier. Theoretical results are derived for elliptically symmetric distributions, while comparison for non-symmetric distributions is conducted by means of a simulation study. Comparisons are conducted for both theoretical classifiers and their empirical counterparts. The performance of the newly proposed classifiers is also compared to the performance of several standard methods in some real life situations.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
<a href="/en/project/GA15-06991S" target="_blank" >GA15-06991S: Functional data analysis and related topics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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