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bayesian inference

Mathematical Definition of Heuristic Causal Inference: What differentiates DAGs and do-calculus?

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Preamble David Hume (Wikipedia)Experimental design is not a new concept and randomised control trials (RCTs) are our solid gold standard of doing quantitative research, when no apparent physical laws are available to validate observations.  However, it is very expensive to design RCTs, not ethical...

causality applied mathematics dags graph theory causal inference randomness heuristic intervention random control trials counterfactual bayesian inference

The concept of overgeneralisation and goodness of rank : Overfitting is not about comparing training and test learning curves

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Preamble     Walt Disney Hall, Los Angeles  (Wikipedia)Unfortunately, it is still thought in machine learning classes that overfitting can be detected by comparing training and test learning curves on the single model's performance.  The origins of this misconception is unknown. Looks like an...

machine learning stat interpretable machine learning connectionist learning overgenearlisation bayesian inference

The conditional query fallacy: Applying Bayesian inference from discrete mathematics perspective

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Preamble    The Tilled Field, Joan Miró (Wikipedia)One of the core concepts in data sciences is conditional probabilities, $p(x|y)$ appear as logical description of many of the tasks, such as formulating regression or as a core concept in Bayesian Inference. However, there is operationally no...

machine learning data science deep learning conditional data mining bayesianism discrete mathematics mathematical beauty mathematical philosophy bayesian inference