Utilization of Singularity Exponent in Nearest Neighbor Based Classifier

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F13%3A00375796" target="_blank" >RIV/67985807:_____/13:00375796 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21460/13:00214975

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Utilization of Singularity Exponent in Nearest Neighbor Based Classifier

Popis výsledku v původním jazyce

Classifiers serve as tools for classifying data into classes. They directly or indirectly take a distribution of data points around a given query point into account. To express the distribution of points from the viewpoint of distances from a given point, a probability distribution mapping function is introduced here. The approximation of this function in a form of a suitable power of the distance is presented. How to state this power - the distribution mapping exponent -- is described. This exponent isused for probability density estimation in high-dimensional spaces and for classification. A close relation of the exponent to a singularity exponent is discussed. It is also shown that this classifier exhibits significantly better behavior (classification accuracy) than other kinds of classifiers for some tasks.

Název v anglickém jazyce

Utilization of Singularity Exponent in Nearest Neighbor Based Classifier

Popis výsledku anglicky

Classifiers serve as tools for classifying data into classes. They directly or indirectly take a distribution of data points around a given query point into account. To express the distribution of points from the viewpoint of distances from a given point, a probability distribution mapping function is introduced here. The approximation of this function in a form of a suitable power of the distance is presented. How to state this power - the distribution mapping exponent -- is described. This exponent isused for probability density estimation in high-dimensional spaces and for classification. A close relation of the exponent to a singularity exponent is discussed. It is also shown that this classifier exhibits significantly better behavior (classification accuracy) than other kinds of classifiers for some tasks.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Classification

ISSN

0176-4268

e-ISSN

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Svazek periodika

30

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

27

Strana od-do

3-29

Kód UT WoS článku

000315441300002

EID výsledku v databázi Scopus

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