Correlation Dimension Estimation for Classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F06%3A00153911" target="_blank" >RIV/68407700:21460/06:00153911 - 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
Correlation Dimension Estimation for Classification
Original language description
In this paper we introduce a new approach that utilizes the correlation dimension (CD) both for probability density estimate of data and consequently for classification. It will be shown that just a classifier utilizing CD exhibits significantly better behavior (classification accuracy) then other kinds of classifiers. Correlation dimension is used for complexity estimation of fractals or any other data generating processes. Basic idea was introduced in the well known paper by Grassberger and Procacciaand there are papers dealing with the correlation dimension estimation. Some experiments that use the correlation dimension for classification has been published too. The idea of correlation dimension classifier directly follows the principle of classifier, which uses the distribution mapping exponent (DME). It is shown that CD-based classifier outperforms DME classifier and many classifiers published on Machine Learning Repository pages.
Czech name
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Czech description
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Publication year
2006
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
The 8th International Conference on Artificial Intelligence and Soft Computing
ISBN
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ISSN
1895-8648
e-ISSN
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Number of pages
11
Pages from-to
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Publisher name
Held
Place of publication
Zakopané
Event location
Zakopane
Event date
Jun 25, 2006
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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