Bayesian methods treat parameters as random variables and define probability as "degrees of belief" (that is, the probability of an event is the degree to which you believe the event is true). When performing a Bayesian analysis, you begin with a prior belief regarding the probability distributi...
Why is machine learning important? Resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. Things like growing volumes and varieties of available data, computational processing that is cheaper and more powerful, ...
Nevertheless, efforts to describe the associations between exposures (such as the show) and health outcomes in different regions are important because consistent findings across studies may help to clarify if the associations may be causal. The current study is crucial to that effort as it overcomes...
It presents the mechanics of Bayesian inference along with the underlying theoretical justification. The chapter highlights important philosophical and practical differences between Bayesian methods and the traditional forms. Three important branches of statistical reasoning are frequentists, Bayesians, ...
After the Axial Age, the West moved toward continuous disunity, but China had successfully maintained a persistent unity pattern. Conventional case (history event) studies are subject to selection bias and theoretical frameworks, which is not objective n
1995. Causal structure in categorization. Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society, Pittsburgh, PA, pp. 521-526] recently proposed a causal status hypothesis which states that features that play a causal role in a relational structure are more central than th...
*In this post I’m going to discuss frequentist inferential statistics, or traditional “null-hypothesis significance testing”. I’ll leave aside debates about whether Bayesian methods are superior and whether P-values get misapplied (see mydefence of the P-value). I’m going to refrain from ...
INTRODUCTIONRegistration is a universal problem which must be addressed in almost all computer-assisted or image-guided surgical systems. It is equally important in orthopaedics, neurosurgery, spine surgery,cranio-facial surgery, or any speciality in which computer-assisted surgical techniques are employed...
Why is predictive analytics important? Organizations are turning to predictive analytics to help solve difficult problems and uncover new opportunities. Common uses include: Detecting fraud.Combining multiple analytics methods can improve pattern detection, identify criminal behavior andprevent fraud. As cyber...
Natural language processing helps computers communicate with humans in their own language and scales other language-related tasks. For example, NLP makes it possible for computers to read text, hear speech, interpret it, measure sentiment and determine which parts are important. ...