Is On-Line Data Analysis Safety? Pitfalls Steaming from
Automated Processing of Heterogeneous Environmental Data and
Possible Solutions

D 2011

Is On-Line Data Analysis Safety? Pitfalls Steaming from Automated Processing of Heterogeneous Environmental Data and Possible Solutions

JARKOVSKÝ, Jiří; Ladislav DUŠEK a Eva JANOUŠOVÁ

Základní údaje

Originální název

Is On-Line Data Analysis Safety? Pitfalls Steaming from Automated Processing of Heterogeneous Environmental Data and Possible Solutions

Autoři

JARKOVSKÝ, Jiří ; Ladislav DUŠEK a Eva JANOUŠOVÁ

Vydání

Neuveden, Environmental Software Systems: Frameworks of Environment, IFIP Advances in Information and Communication Technology, vol. 359, od s. 486-490, 5 s. 2011

Nakladatel

Springer

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

30000 3. Medical and Health Sciences

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

paměťový nosič (CD, DVD, flash disk)

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14110/11:00052824

Organizační jednotka

Lékařská fakulta

ISBN

978-3-642-22284-9

ISSN

UT WoS

000306579200052

Klíčová slova anglicky

classification; nonparametric multivariate analysis; heterogeneous data

Změněno: 22. 1. 2014 23:58, RNDr. Eva Koriťáková, Ph.D.

Anotace

V originále

The current situation in environmental monitoring is characterized by increasing amount of data from monitoring networks together with increasing requirements on joining of these data from various sources in comprehensive databases and their usage for decision support in environmental protection and management. The automated analysis of such a heterogeneous datasets is a complicated process, rich in statistical pitfalls. There is a number of methods for multivariate classification of objects, e.g. logistic regression, discriminant analysis or neural networks; however, most of commonly used classification techniques have prerequisites about distribution of data, are computationally demanding or their model can be considered as “black box”. Keeping these facts in mind, we attempted to develop a robust multivariate method suitable for classification of unknown cases with minimum sensitivity to data distribution problems; and thus, suitable for routine use in practice.

Citovat

JARKOVSKÝ, Jiří; Ladislav DUŠEK a Eva JANOUŠOVÁ. Is On-Line Data Analysis Safety? Pitfalls Steaming from Automated Processing of Heterogeneous Environmental Data and Possible Solutions. In Jiří Hřebíček, Gerald Schimak, Ralf Denzer. Environmental Software Systems: Frameworks of Environment, IFIP Advances in Information and Communication Technology, vol. 359. Neuveden: Springer, 2011, s. 486-490. ISBN 978-3-642-22284-9.

@inproceedings{947162,
   author = {Jarkovský, Jiří and Dušek, Ladislav and Janoušová, Eva},
   address = {Neuveden},
   booktitle = {Environmental Software Systems: Frameworks of Environment, IFIP Advances in Information and Communication Technology, vol. 359},
   editor = {Jiří Hřebíček, Gerald Schimak, Ralf Denzer},
   keywords = {classification; nonparametric multivariate analysis; heterogeneous data},
   howpublished = {paměťový nosič},
   language = {eng},
   location = {Neuveden},
   isbn = {978-3-642-22284-9},
   pages = {486-490},
   publisher = {Springer},
   title = {Is On-Line Data Analysis Safety? Pitfalls Steaming from Automated Processing of Heterogeneous Environmental Data and Possible Solutions},
   year = {2011}
}

TY  - CONF
ID  - 947162
AU  - Jarkovský, Jiří - Dušek, Ladislav - Janoušová, Eva
PY  - 2011
TI  - Is On-Line Data Analysis Safety? Pitfalls Steaming from Automated Processing of Heterogeneous Environmental Data and Possible Solutions
PB  - Springer
CY  - Neuveden
SN  - 9783642222849
KW  - classification
KW  - nonparametric multivariate analysis
KW  - heterogeneous data
N2  - The current situation in environmental monitoring is characterized by increasing amount of data from monitoring networks together with increasing requirements on joining of these data from various sources in comprehensive databases and their usage for decision support in environmental protection and management. The automated analysis of such a heterogeneous datasets is a complicated process, rich in statistical pitfalls. There is a number of methods for multivariate classification of objects, e.g. logistic regression, discriminant analysis or neural networks; however, most of commonly used classification techniques have prerequisites about distribution of data, are computationally demanding or their model can be considered as “black box”. Keeping these facts in mind, we attempted to develop a robust multivariate method suitable for classification of unknown cases with minimum sensitivity to data distribution problems; and thus, suitable for routine use in practice.
ER  -

JARKOVSKÝ, Jiří; Ladislav DUŠEK a Eva JANOUŠOVÁ. Is On-Line Data Analysis Safety? Pitfalls Steaming from Automated Processing of Heterogeneous Environmental Data and Possible Solutions. In Jiří Hřebíček, Gerald Schimak, Ralf Denzer. \textit{Environmental Software Systems: Frameworks of Environment, IFIP Advances in Information and Communication Technology, vol. 359}. Neuveden: Springer, 2011, s.~486-490. ISBN~978-3-642-22284-9.

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