text.skipToContent text.skipToNavigation
background-image

Algorithmic Learning in a Random World von Vovk, Vladimir (eBook)

  • Erscheinungsdatum: 05.12.2005
  • Verlag: Springer-Verlag
eBook (PDF)
130,89 €
inkl. gesetzl. MwSt.
Sofort per Download lieferbar

Online verfügbar

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. Based 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.

Produktinformationen

    Format: PDF
    Kopierschutz: AdobeDRM
    Seitenzahl: 324
    Erscheinungsdatum: 05.12.2005
    Sprache: Englisch
    ISBN: 9780387250618
    Verlag: Springer-Verlag
    Größe: 15711kBytes
Weiterlesen weniger lesen

Kundenbewertungen