PyRational

I have implemented a Python library for modelling, inference and updating with Almost Desirable Gambles (ADG) models. It is both friendly and flexible. It works with continuous, discrete and mixed variables. Here you can find some additional info, setup instructions and 4 examples (notebooks): https://github.com/PyRational/PyRational/blob/master/notebooks/index.ipynb The notebooks (and relative examples) …

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Baycomp

Janez Demsar has reimplemented our library about Bayesian hypothesis testing for comparing competing algorithms in ML. It can now be installed directly with pip. Hereafter, a brief description. Baycomp is a library for Bayesian comparison of classifiers. Functions compare two classifiers on one or on multiple data sets. They compute …

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Bayes+Hilbert=QM

QM is based on four main axioms, which were derived after a long process of trial and error. The motivations for the axioms are not always clear and even to experts the basic axioms of QM often appear counter-intuitive. In a recent paper [1], we have shown that: It is …

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The importance of the region of practical equivalence (ROPE)

The difference between two classifiers (algorithms) can be very small; however there are no two classifiers whose accuracies are perfectly equivalent. By using an null hypothesis significance test (NHST), the null hypothesis is that the classifiers are equal. However, the null hypothesis is practically always false! By rejecting the null …

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