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

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JARKOVSKÝ Jiří DUŠEK Ladislav JANOUŠOVÁ Eva

Rok publikování 2011
Druh Článek ve sborníku
Konference Environmental Software Systems: Frameworks of Environment, IFIP Advances in Information and Communication Technology, vol. 359
Fakulta / Pracoviště MU

Lékařská fakulta

Citace
Obor Ostatní lékařské obory
Klíčová slova classification; nonparametric multivariate analysis; heterogeneous data
Popis 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.

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