A Priori and A Posteriori Machine Learning and Nonlinear Artificial Neural Networks View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2010

AUTHORS

Jan Zelinka , Jan Romportl , Luděk Müller

ABSTRACT

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. More... »

PAGES

472-479

References to SciGraph publications

  • 2002-06. A Perspective View and Survey of Meta-Learning in ARTIFICIAL INTELLIGENCE REVIEW
  • Book

    TITLE

    Text, Speech and Dialogue

    ISBN

    978-3-642-15759-2
    978-3-642-15760-8

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-15760-8_60

    DOI

    http://dx.doi.org/10.1007/978-3-642-15760-8_60

    DIMENSIONS

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