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Progress in Artificial Intelligence
Erschienen in: Progress in Artificial Intelligence 1/2018

08.06.2017 | Regular Paper

Impact of time series discretization on intensive care burn unit survival classification

verfasst von: Isidoro J. Casanova, Manuel Campos, Jose M. Juarez, Antonio Fernandez-Fernandez-Arroyo, Jose A. Lorente

Erschienen in: Progress in Artificial Intelligence | Ausgabe 1/2018

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Abstract

In the preprocessing step of a knowledge discovery process, the method of discretization selected can have a remarkable impact on the performance and accuracy of classification algorithms. In this article, we analyze and compare expert discretization and automatic discretization algorithms. In particular, we study their impact to predict the survival of patients in the context of intensive care burn units. We focus on the quality of different discretizations algorithm analyzing the number of intervals generated, the amount of patterns produced and the classification performance in a specific clinical problem. Our results show that the many algorithms underperform expert discretization and that it is necessary to take into account the correlation among continuous features to obtain the best accuracy.
Vorheriger Artikel Scatter search for the bi-criteria p-median p-dispersion problem
Nächster Artikel Improvement of subgroup descriptions in noisy data by detecting exceptions

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Metadaten
Titel
Impact of time series discretization on intensive care burn unit survival classification
verfasst von
Isidoro J. Casanova
Manuel Campos
Jose M. Juarez
Antonio Fernandez-Fernandez-Arroyo
Jose A. Lorente
Publikationsdatum
08.06.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Progress in Artificial Intelligence / Ausgabe 1/2018
Print ISSN: 2192-6352
Elektronische ISSN: 2192-6360
DOI
https://doi.org/10.1007/s13748-017-0130-8

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