Gaussian Complexities Based Decision Tree Pruning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F04%3A03096739" target="_blank" >RIV/68407700:21230/04:03096739 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Gaussian Complexities Based Decision Tree Pruning

Original language description

We investigate a method for pruning of decision trees based on the complexity measure of a tree and its error rate. It uses the Gaussian complexity averages of a decision tree to estimate the error rate of classification. This complexity measure is data-dependent, so we expect it to allow the pruning to capture the dependencies in the data better than error based pruning methods or general complexity based pruning methods. We perform experiments that compare unpruned decision tree, decision tree prunedwith our method and decision tree pruned with Reduced Error Pruning method. Our results show that proposed method outperforms both mentioned methods

Czech name

Není k dispozici

Czech description

Není k dispozici

Type

D - Article in proceedings

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2004

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Cybernetics and Systems 2004

ISBN

3-85206-169-5

ISSN

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e-ISSN

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Number of pages

4

Pages from-to

719-722

Publisher name

Austrian Society for Cybernetics Studies

Place of publication

Vienna

Event location

Vienna

Event date

Apr 13, 2004

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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