supervised learning

Jan 28 2023

Misconceptions on non-temporal learning: When do machine learning models qualify as prediction systems?

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Preamble    Babylonian Tablet for square root of 2. (Wikipedia)Prediction implies a mechanics, as in knowing a form of a trajectory over time.  Strictly speaking a predictive system implies knowing a solution to the path, set of variable depending on time, time evolution of the system under...

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Jun 20 2022

Empirical risk minimization is not learning : A mathematical definition of learning and re-understanding of overfitting and Occam's razor in machine learning

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Simionescu Function (Wikipedia)PreambleThe holy grail of machine learning appears to be the empirical risk minimisation. However, on the contrary to general dogma,  the primary objective of machine learning is not risk minimisation per se but mimicking human or animal learning. Empirical risk...

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Dec 29 2020

Practice causal inference: Conventional supervised learning can't do inference

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Domino OR-gate (Wikipedia)PreambleA trained model may provide predictions about input values it may never seen before but it isn't an inference, at least for 'classical' supervised learning. In reality it provides an interpolation from the training-set, i.e., via function...

machine learning causality supervised learning inference causal inference

Feb 23 2020

A simple and interpretable performance measure for a binary classifier

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Kindly reposted to KDnuggets by Gregory Piatetsky-Shapiro  Preamble The core application of machine learning models is a binary classification task. This appears in polyhedra of areas from medicine for diagnostic tests to credit risk decision making for consumers.  Techniques in building...

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Jan 03 2019

Core principles of sustainable data science, machine learning and AI product development: Research as a core driver

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Kindly reposto to KDnuggets  by Gregory Piatetsky-Shapiro Preamble  Almost all businesses and industry embraced Machine learning (ML) technologies. Apart from ROI concerns, as it is an expensive endeavour to develop and deploy a service driven by ML techniques, sustainability as in going beyond...

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Nov 17 2017

Teaching to machines: What is learning in machine learning entails?

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Preamble Ebbinghaus (WikipediaMachine Learning (ML) is now a de-facto skill for every quantitative job and almost every industry embraced it, even though fundamentals of the field is not new at all. However, what does it mean to teach to a machine? Unfortunately, for even moderate technical people...

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Aug 16 2017

Understanding overfitting: an inaccurate meme in supervised learning

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Kindly reposted to KDnuggets by Gregory Piatetsky-Shapiro with the title Understanding overfitting: an inaccurate meme in machine learning Preamble There is a lot of confusion among practitioners regarding the concept of overfitting. It seems like, a kind of an urban legend or a meme, a folklore...

machine learning data science prediction statistical learning supervised learning gnu r cross-validation overtraining r programming overfitting regression statistics r r project regularisation