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INDUCTION, PROBABILITY, AND BAYESIAN EPISTEMOLOGY
2003In the last sixty years Finnish analytical philosophers have been extensively investigating induction and probability, and their role in empirical sciences. In this paper the main lines and outcomes of such studies are examined. In particular, the following issues are considered: von Wright’s theory of inductive elimination and his analysis of ...
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ON BAYESIAN LOGICAL PROBABILITY
ETS Research Bulletin Series, 1964ABSTRACTIn a recent paper (Edwards, Lindman, and Savage, 1963), psychologists have been urged to adopt a Bayesian personal probability approach to statistical inference. The purpose of this paper is to suggest that a Bayesian logical probability approach may be superior to the personal probability approach.
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Probabilities: Bayesian Classifiers
2015The earliest attempts to predict an example’s class based on the known attribute values go back to well before World War II—prehistory, by the standards of computer science. Of course, nobody used the term “machine learning,” in those days, but the goal was essentially the same as the one addressed in this book.
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Determining the conditional probabilities in Bayesian networks
2003Summary: Bayesian networks are used to illustrate how the probability of having a disease can be updated given the results from clinical tests. The problem of diagnosis, that is of determining whether a certain disease is present, \(D\), or absent, \(D'\), based on the result of a medical test, is discussed.
OLMUŞ, Hülya, ERBAŞ, S. Oral
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Bayesian Approach to Probability
2016The Bayesian approach to probability allows to define in a quantitative way probabilities associated to statement whose truth or falsity is not known. This also applies to the knowledge of unknown parameters in physics, allowing to assign a probability to the possibility that a parameter’s value lies within a certain interval.
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Bayesian Probability Approach to ADHD Appraisal
2009Accurate diagnosis of attentional disorders such as attention-deficit hyperactivity disorder (ADHD) is imperative because there are multiple negative psychosocial sequelae related to undiagnosed and untreated ADHD. Early and accurate detection can lead to effective intervention and prevention of negative sequelae.
Raina, Robeva, Jennifer Kim, Penberthy
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Probability and Bayesian Statistics.
The Statistician, 1989P. M. Lee, R. Viertl
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Bayesian learning for neural networks: an algorithmic survey
Artificial Intelligence Review, 2023Alexandros Iosifidis
exaly