Algorithmic Learning in a Random World Pdf

Edition: 2005
Release: 2005-03-22
Publisher: Springer
Binding: Hardcover
ISBN/ASIN: 0387001522



Algorithmic Learning in a Random World

Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Free download Algorithmic Learning in a Random World books collection in PDF, EPUB, FB2, MOBI, and TXT formats. B Best deals ebooks download Algorithmic Learning in a Random World on amazon.sed on these approximations, a new set of machine learning algorithms have been developed that can be used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data are independent and identically distributed (assumption of randomness). Another aim of this unique monograph is to outline some limits of predictions: The approach based on algorithmic theory of randomness allows for the proof of impossibility of prediction in certain situations. The book describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness. Algorithmic Learning in a Random World with free ebook downloads available via rapidshare, mediafire, 4shared, and hotfile.

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