Self-Learning Linear Models
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).
KeywordsOrdinary Little Square Posterior Distribution Prior Distribution Bayesian Inference Linear Regression Model
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