Geodesic
$k$-Depth-nearest Neighbour Method and its Performance on Skew-normal Distributons
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica, Tome 52 (2013) no. 2, pp. 121-129 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

Voir la notice de l'article

In the present paper we investigate performance of the $k$-depth-nearest classifier. This classifier, proposed recently by Vencálek, uses the concept of data depth to improve the classification method known as the $k$-nearest neighbour. Simulation study which is presented here deals with the two-class classification problem in which the considered distributions belong to the family of skewed normal distributions.
In the present paper we investigate performance of the $k$-depth-nearest classifier. This classifier, proposed recently by Vencálek, uses the concept of data depth to improve the classification method known as the $k$-nearest neighbour. Simulation study which is presented here deals with the two-class classification problem in which the considered distributions belong to the family of skewed normal distributions.
Classification : 62G30, 62H30
Keywords: data depth; classification; k-nearest neighbour; skewed normal distribution 
@article{AUPO_2013_52_2_a10,
     author = {Venc\'alek, Ond\v{r}ej},
     title = {$k${-Depth-nearest} {Neighbour} {Method} and its {Performance} on {Skew-normal} {Distributons}},
     journal = {Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica},
     pages = {121--129},
     year = {2013},
     volume = {52},
     number = {2},
     mrnumber = {3202385},
     zbl = {06296020},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/AUPO_2013_52_2_a10/}
}
TY  - JOUR
AU  - Vencálek, Ondřej
TI  - $k$-Depth-nearest Neighbour Method and its Performance on Skew-normal Distributons
JO  - Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
PY  - 2013
SP  - 121
EP  - 129
VL  - 52
IS  - 2
UR  - http://geodesic.mathdoc.fr/item/AUPO_2013_52_2_a10/
LA  - en
ID  - AUPO_2013_52_2_a10
ER  - 
%0 Journal Article
%A Vencálek, Ondřej
%T $k$-Depth-nearest Neighbour Method and its Performance on Skew-normal Distributons
%J Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
%D 2013
%P 121-129
%V 52
%N 2
%U http://geodesic.mathdoc.fr/item/AUPO_2013_52_2_a10/
%G en
%F AUPO_2013_52_2_a10
Vencálek, Ondřej. $k$-Depth-nearest Neighbour Method and its Performance on Skew-normal Distributons. Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica, Tome 52 (2013) no. 2, pp. 121-129. http://geodesic.mathdoc.fr/item/AUPO_2013_52_2_a10/