Full metadata record
| DC pole | Hodnota | Jazyk |
|---|---|---|
| dc.contributor.author | Zelinka, Jan | |
| dc.contributor.author | Romportl, Jan | |
| dc.contributor.author | Müller, Luděk | |
| dc.date.accessioned | 2016-01-07T10:56:03Z | |
| dc.date.available | 2016-01-07T10:56:03Z | |
| dc.date.issued | 2010 | |
| dc.identifier.citation | ZELINKA, Jan; ROMPORTL, Jan; MÜLLER, Luděk. A priori and a posteriori machine learning and nonlinear artificial neural networks. In: Progress in pattern recognition, image analysis, computer vision, and applications. Berlin: Springer, 2010, p. 472-479. (Lectures notes in computer science; 6231). ISBN 978-3-642-15759-2. | en |
| dc.identifier.isbn | 978-3-642-15759-2 | |
| dc.identifier.uri | http://www.kky.zcu.cz/cs/publications/JanZelinka_2010_APrioriandA | |
| dc.identifier.uri | http://hdl.handle.net/11025/17159 | |
| dc.format | 8 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | Springer | en |
| dc.relation.ispartofseries | Lecture notes in computer science; 6231 | en |
| dc.rights | © Jan Zelinka - Jan Romportl - Luděk Müller | cs |
| dc.subject | umělá neuronová síť | cs |
| dc.subject | strojové učení | cs |
| dc.title | A priori and a posteriori machine learning and nonlinear artificial neural networks | en |
| dc.title.alternative | Apriorní a aposteriorní Machine Learning a ANN | cs |
| dc.type | článek | cs |
| dc.type | article | en |
| dc.rights.access | openAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | The main idea of a priori machine learning is to apply a machine learning method on a machine learning problem itself.We call it "a priori" because the processed data set does not originate from any measurement or other observation.Machine learning which deals with any observation is called "posterior". The paper describes how posterior machine learning can be modified by a priori machine learning. A priori and posterior machine learning algorithms are proposed for artificial neural network training and are tested in the task of audio-visual phoneme classification. | en |
| dc.subject.translated | artificial neural network | en |
| dc.subject.translated | machine learning | en |
| dc.type.status | Peer-reviewed | en |
| Vyskytuje se v kolekcích: | Články / Articles (MMI) Články / Articles (KKY) | |
Soubory připojené k záznamu:
| Soubor | Popis | Velikost | Formát | |
|---|---|---|---|---|
| JanZelinka_2010_APrioriandA.pdf | Plný text | 166,56 kB | Adobe PDF | Zobrazit/otevřít |
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