Mixture Initialization Based on Prior Data Visual Analysis

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F19%3A00491347" target="_blank" >RIV/67985556:_____/19:00491347 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-78931-6_3" target="_blank" >http://dx.doi.org/10.1007/978-3-319-78931-6_3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-78931-6_3" target="_blank" >10.1007/978-3-319-78931-6_3</a>

Result language
angličtina
Original language name
Mixture Initialization Based on Prior Data Visual Analysis
Original language description
The initialization is known to be a critical task for running a mixture estimation algorithm. A majority of approaches existing in the literature are related to initialization of the expectation-maximization algorithm widely used in this area. This study focuses on the initialization of the recursive mixture estimation for the case of normal components, where the mentioned methods are not applicable. Its key part is a choice of the initial statistics of normal components.
Czech name
—
Czech description
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Project
<a href="/en/project/GA15-03564S" target="_blank" >GA15-03564S: Clustering and classification using recursive mixture estimation</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name
Intuitionistic Fuzziness and Other Intelligent Theories and Their Applications
ISBN
978-3-319-78930-9
Number of pages of the result
21
Pages from-to
29-49
Number of pages of the book
193
Publisher name
Springer
Place of publication
Cham
UT code for WoS chapter
—

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