cross-validation – Andrew Fairless, Ph.D.

What I Read: Bayesian Mixed Models

By Andrew Fairless on March 26, 2025December 8, 2024

https://towardsdatascience.com/evaluating-bayesian-mixed-models-in-r-python-27d344a03016?gi=e23f7abbacbf Evaluating Bayesian Mixed Models in R/PythonEduardo Coronado SrokaJul 3, 2020 “…model checking and evaluation are just one of those things you can’t (and shouldn’t) avoid… Yet, I think inContinue readingWhat I Read: Bayesian Mixed Models

What I Read: Competitive Machine Learning

By Andrew Fairless on May 9, 2023March 30, 2023

https://mlcontests.com/state-of-competitive-machine-learning-2022/ The State of Competitive Machine Learning2022 Edition “We summarise the state of the competitive landscape and analyse the 200+ competitions that took place in 2022. Plus a deep diveContinue readingWhat I Read: Competitive Machine Learning

What I Read: Concept Drift Without Labeled Data

By Andrew Fairless on September 26, 2022August 22, 2022

https://concept-drift.fastforwardlabs.com/ Inferring Concept Drift Without Labeled DataFF22Aug 2021 “…we explore broadly applicable approaches for dealing with concept drift when labeled data is not readily accessible. We’ll start by defining whatContinue readingWhat I Read: Concept Drift Without Labeled Data

What I Read: cross-validation

By Andrew Fairless on August 16, 2022July 18, 2022

https://robjhyndman.com/hyndsight/crossvalidation/ Why every statistician should know about cross-validationHyndsightRob J Hyndman4 October 2010 “Why every statistician should know about cross-validation”

What I Read: evaluate online machine learning models

By Andrew Fairless on March 14, 2022January 20, 2022

https://maxhalford.github.io/blog/online-learning-evaluation/ The correct way to evaluate online machine learning modelsMax Halford2020-06-07 “Batch models are meant to be used when you can afford to retrain your model from scratch every soContinue readingWhat I Read: evaluate online machine learning models

What I Read: Double Machine Learning for causal inference

By Andrew Fairless on July 21, 2021July 2, 2021

https://towardsdatascience.com/double-machine-learning-for-causal-inference-78e0c6111f9d Double Machine Learning for causal inferenceHow Double Machine Learning for causal inference works, from the theoretical foundations to an example of application.Borja VelascoJun 25 “This post tries to explain,Continue readingWhat I Read: Double Machine Learning for causal inference

What I Read: Can you trust AutoML?

By Andrew Fairless on February 26, 2021February 18, 2021

https://medium.com/analytics-vidhya/can-you-trust-automl-3a02332e66a0 Can you trust AutoML?Ioannis TsamardinosDec 2 “AutoML platforms try hundreds or even thousands of different ML pipelines… Do existing AutoML libraries and platforms return reliable estimates of the performanceContinue readingWhat I Read: Can you trust AutoML?

Tag: cross-validation