Adjusting parameters of the classifiers in multiclass classification

Daniel Kostrzewa; Robert Brzeski

doi:10.1007/978-3-319-58274-0_8

Adjusting parameters of the classifiers in multiclass classification

Department of Applied Informatics (RAU/RAU7)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

The article presents the results of the optimization process of classification for five selected data sets. These data sets contain the data for the realization of the multiclass classification. The article presents the results of initial classification, carried out by dozens of classifiers, as well as the results after the process of adjusting parameters, this time obtained for a set of selected classifiers. At the end of article, a summary and the possibility of further work are provided.

Original language	English
Title of host publication	Beyond Databases, Architectures and Structures
Subtitle of host publication	Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings
Editors	Stanislaw Kozielski, Dariusz Mrozek, Pawel Kasprowski, Bozena Malysiak-Mrozek, Daniel Kostrzewa
Publisher	Springer Verlag
Pages	89-101
Number of pages	13
ISBN (Print)	9783319582733
DOIs	https://doi.org/10.1007/978-3-319-58274-0_8
Publication status	Published - 2017
Event	13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017 - Ustron, Poland Duration: 30 May 2017 → 2 Jun 2017

Publication series

Name	Communications in Computer and Information Science
Volume	716
ISSN (Print)	1865-0929

Conference

Conference	13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017
Country/Territory	Poland
City	Ustron
Period	30/05/17 → 2/06/17

Keywords

Classification
DIGITS
GCM
Kappa
Multiclass
PEMS
SMARTPHONE
UCI
URBAN
Weka

ASJC Scopus subject areas

General Computer Science
General Mathematics

Access to Document

10.1007/978-3-319-58274-0_8

Cite this

Kostrzewa, D., & Brzeski, R. (2017). Adjusting parameters of the classifiers in multiclass classification. In S. Kozielski, D. Mrozek, P. Kasprowski, B. Malysiak-Mrozek, & D. Kostrzewa (Eds.), Beyond Databases, Architectures and Structures: Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings (pp. 89-101). (Communications in Computer and Information Science; Vol. 716). Springer Verlag. https://doi.org/10.1007/978-3-319-58274-0_8

Kostrzewa, Daniel ; Brzeski, Robert. / Adjusting parameters of the classifiers in multiclass classification. Beyond Databases, Architectures and Structures: Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings. editor / Stanislaw Kozielski ; Dariusz Mrozek ; Pawel Kasprowski ; Bozena Malysiak-Mrozek ; Daniel Kostrzewa. Springer Verlag, 2017. pp. 89-101 (Communications in Computer and Information Science).

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title = "Adjusting parameters of the classifiers in multiclass classification",

abstract = "The article presents the results of the optimization process of classification for five selected data sets. These data sets contain the data for the realization of the multiclass classification. The article presents the results of initial classification, carried out by dozens of classifiers, as well as the results after the process of adjusting parameters, this time obtained for a set of selected classifiers. At the end of article, a summary and the possibility of further work are provided.",

keywords = "Classification, DIGITS, GCM, Kappa, Multiclass, PEMS, SMARTPHONE, UCI, URBAN, Weka",

author = "Daniel Kostrzewa and Robert Brzeski",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017 ; Conference date: 30-05-2017 Through 02-06-2017",

year = "2017",

doi = "10.1007/978-3-319-58274-0\_8",

language = "English",

isbn = "9783319582733",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

pages = "89--101",

editor = "Stanislaw Kozielski and Dariusz Mrozek and Pawel Kasprowski and Bozena Malysiak-Mrozek and Daniel Kostrzewa",

booktitle = "Beyond Databases, Architectures and Structures",

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Kostrzewa, D & Brzeski, R 2017, Adjusting parameters of the classifiers in multiclass classification. in S Kozielski, D Mrozek, P Kasprowski, B Malysiak-Mrozek & D Kostrzewa (eds), Beyond Databases, Architectures and Structures: Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings. Communications in Computer and Information Science, vol. 716, Springer Verlag, pp. 89-101, 13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017, Ustron, Poland, 30/05/17. https://doi.org/10.1007/978-3-319-58274-0_8

Adjusting parameters of the classifiers in multiclass classification. / Kostrzewa, Daniel ; Brzeski, Robert.
Beyond Databases, Architectures and Structures: Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings. ed. / Stanislaw Kozielski; Dariusz Mrozek; Pawel Kasprowski; Bozena Malysiak-Mrozek; Daniel Kostrzewa. Springer Verlag, 2017. p. 89-101 (Communications in Computer and Information Science; Vol. 716).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Adjusting parameters of the classifiers in multiclass classification

AU - Kostrzewa, Daniel

AU - Brzeski, Robert

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - The article presents the results of the optimization process of classification for five selected data sets. These data sets contain the data for the realization of the multiclass classification. The article presents the results of initial classification, carried out by dozens of classifiers, as well as the results after the process of adjusting parameters, this time obtained for a set of selected classifiers. At the end of article, a summary and the possibility of further work are provided.

AB - The article presents the results of the optimization process of classification for five selected data sets. These data sets contain the data for the realization of the multiclass classification. The article presents the results of initial classification, carried out by dozens of classifiers, as well as the results after the process of adjusting parameters, this time obtained for a set of selected classifiers. At the end of article, a summary and the possibility of further work are provided.

KW - Classification

KW - DIGITS

KW - GCM

KW - Kappa

KW - Multiclass

KW - PEMS

KW - SMARTPHONE

KW - UCI

KW - URBAN

KW - Weka

UR - https://www.scopus.com/pages/publications/85019768505

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DO - 10.1007/978-3-319-58274-0_8

M3 - Conference contribution

AN - SCOPUS:85019768505

SN - 9783319582733

T3 - Communications in Computer and Information Science

SP - 89

EP - 101

BT - Beyond Databases, Architectures and Structures

A2 - Kozielski, Stanislaw

A2 - Mrozek, Dariusz

A2 - Kasprowski, Pawel

A2 - Malysiak-Mrozek, Bozena

A2 - Kostrzewa, Daniel

PB - Springer Verlag

T2 - 13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017

Y2 - 30 May 2017 through 2 June 2017

ER -

Kostrzewa D , Brzeski R. Adjusting parameters of the classifiers in multiclass classification. In Kozielski S, Mrozek D, Kasprowski P, Malysiak-Mrozek B, Kostrzewa D, editors, Beyond Databases, Architectures and Structures: Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings. Springer Verlag. 2017. p. 89-101. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-58274-0_8

Adjusting parameters of the classifiers in multiclass classification

Abstract

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Keywords

ASJC Scopus subject areas

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