Title: | A priori and a posteriori machine learning and nonlinear artificial neural networks |
Other Titles: | Apriorní a aposteriorní Machine Learning a ANN |
Authors: | Zelinka, Jan Romportl, Jan Müller, Luděk |
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. |
Issue Date: | 2010 |
Publisher: | Springer |
Document type: | článek article |
URI: | http://www.kky.zcu.cz/cs/publications/JanZelinka_2010_APrioriandA http://hdl.handle.net/11025/17159 |
ISBN: | 978-3-642-15759-2 |
Keywords: | umělá neuronová síť;strojové učení |
Keywords in different language: | artificial neural network;machine learning |
Abstract in different language: | 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. |
Rights: | © Jan Zelinka - Jan Romportl - Luděk Müller |
Appears in Collections: | Články / Articles (MMI) Články / Articles (KKY) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
JanZelinka_2010_APrioriandA.pdf | Plný text | 166,56 kB | Adobe PDF | View/Open |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/17159
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.