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Introducing Uncertainty in Predictive Modeling-Friend or Foe?
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2012 (English)In: Journal of chemical information and modeling, ISSN 1549-9596, Vol. 52, no 11, 2815-2822 p.Article in journal (Refereed) Published
Abstract [en]

Uncertainty was introduced to chemical descriptors of 16 publicly available data. sets to various degrees and in various-ways order to investigate the effect on the predictive performance Of the State of-the-art method decision tree ensembles. A number of strategies to handle uncertainty in:decision tree ensembles were evaluated. The main conclusion of the Study. is that uncertainty to a large extent may be introduced in chemical descriptors without. impairing the predictive performance of ensembles and without the predictive performance being significantly reduced from a practical point of view. The investigation. further showed that even When distributions of uncertain values were provided, the ensembles method could generate equally effective models from single-point samples from these distributions. Hence, there seems to be no advantage in using more., elaborate Methods for handling uncertainty in chemical descriptors when using decision tree ensembles as a modeling method for the considered types of introduced uncertainty.

Place, publisher, year, edition, pages
2012. Vol. 52, no 11, 2815-2822 p.
National Category
Computer and Information Science Chemical Sciences
Identifiers
URN: urn:nbn:se:su:diva-84773DOI: 10.1021/ci3003446ISI: 000311461400003OAI: oai:DiVA.org:su-84773DiVA: diva2:582047
Note

AuthorCount:2;

Available from: 2013-01-03 Created: 2013-01-02 Last updated: 2013-01-03Bibliographically approved

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