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Self-Learning Linear Models

  • Steffen Christ

Absrtact

This chapter covers the theoretical and technical background of the specific learning method later employed in Chapters 6 and 7 to actually forecast latent demand based on its characteristics as described in Chapter 5. The presented method rests on the Bayesian interpretation of probability, which is fundamentally different from the classical or frequentist interpretation, where probabilities are simply viewed “in terms of the frequencies of random, repeatable events” (see, e.g., Bishop, 2006, p. 21).

Keywords

Ordinary Little Square Posterior Distribution Prior Distribution Bayesian Inference Linear Regression Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Gabler Verlag | Springer Fachmedien Wiesbaden GmbH 2011

Authors and Affiliations

  • Steffen Christ

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