Minimum Description Length Principle for Compositional Model Learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F15%3A00507131" target="_blank" >RIV/67985556:_____/15:00507131 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-25135-6_25" target="_blank" >http://dx.doi.org/10.1007/978-3-319-25135-6_25</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-25135-6_25" target="_blank" >10.1007/978-3-319-25135-6_25</a>
Alternative languages
Result language
angličtina
Original language name
Minimum Description Length Principle for Compositional Model Learning
Original language description
Not having another source of information than source data, the process of data-based model construction can be viewed as the transformation of information represented by data into that represented by the model. The paper explains how this idea supports the Minimum Description Length Principle and how it can be employed to avoid the overfitting of the constructed model.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Integrated Uncertainty in Knowledge Modelling and Decision Making
ISBN
978-3-319-25134-9
ISSN
0302-9743
e-ISSN
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Number of pages
13
Pages from-to
254-266
Publisher name
Springer
Place of publication
Cham
Event location
Nha Trang
Event date
Oct 15, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000367593500025