OBJECTIVES The observed posterior probability distributions regarding the benefits of surgery for otitis media with effusion (OME) with expected probability distributions, using Bayes' theorem are compared. METHODS Postal questionnaires were used to assess prior and posterior probability distributions among ear-nose-throat (ENT) surgeons in the Netherlands. RESULTS In their prior probabilit...

AIM The aim in this methodological paper is to demonstrate, using Bayes' Theorem, an approach to estimating the difference in prevalence of a disorder in two groups whose test scores are obtained, illustrated with data from a college student trial where 12-month outcomes are reported for the Alcohol Use Disorders Identification Test (AUDIT). METHOD Using known population prevalence as a backg...

Making use of Bayes' theorem, the method used for calculating proton decay lifetime limits is detailed, with particular emphasis on the prior probability distribution for the background. The method is then applied to various example cases.

Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).

A feeling emerges from reading McGrayne’s book expressed as a paraphrase of verse Hamlet: There are more things behind Bayes’ theorem, Horatio, than dreamt in your philosophy. The tells story the birth and survival an idea around which social enterprises, personal odysseys, human passions masterfully woven by author. has 17 chapters distributed five parts two annexes. These reveal narrative str...

There are numerous text documents available in electronic form. More and more are becoming available every day. Such documents represent a massive amount of information that is easily accessible. Seeking value in this huge collection requires organization; much of the work of organizing documents can be automated through text classification. The accuracy and our understanding of such systems gr...

X1, . . . , Xn iid ∼ N (θ, σ), with σ known. Our goal is to estimate θ under squared-error loss. For our first guess, pick the natural estimator X. Note that it has constant risk σ 2 n , which suggests minimaxity because we know that Bayes estimators with constant risk are also minimax estimators. However, X is not Bayes for any prior, because under squared-error loss unbiased estimators are Ba...

Classification, particularly Text Classification, is a supervised learning approach categorizing into various categories, the available training set of correctly identified observations analyzed into a set of features. There are many phases involved in classification. The main classification phase involves the use of classification algorithms or classifiers. Among the various classifiers, the N...

In the context of irreversible dynamics, associating to a physical process its intuitive reverse can result be quite ambiguous task. It is standard choice define using Bayes' theorem, but, in general, this not optimal. work we explore whether it possible characterise an optimal map building from concept state retrieval maps. doing so, propose set principles that maps should satisfy. We find out...

In this thesis, we study sequences of functions of the form Fp → {0, 1} for varying n, and define a notion of convergence based on the induced distributions from restricting the functions to a random affine subspace. One of the key tools we use is the recently developed theory of ‘higher order Fourier analysis’, where the characters of standard Fourier analysis are replaced with exponentials of...