https://cameronpatrick.com/post/2023/07/mice-in-a-blog-post/ Dirty imputation done dirt cheap: implementing Multiple Imputation by Chained Equations in one blog postCameron Patrick31 July, 2023 “An attempt to understand in detail how Multiple Imputation by Chained
What I Read: missing data mechanisms
https://cameronpatrick.com/post/2023/06/untangling-mar-mcar-mnar/ Understanding missing data mechanisms using causal DAGsCameron PatrickJune 28, 2023 “Correctly analysing datasets that have missing data requires extra care and consideration to produce correct results.”
What I Read: Unsupervised Learning Metrics
https://www.kdnuggets.com/2023/04/exploring-unsupervised-learning-metrics.html Exploring Unsupervised Learning MetricsCornellius Yudha WijayaApril 13, 2023 “This article will discuss the metrics used to evaluate unsupervised machine learning algorithms…”
What I Read: Predict Distributions
https://towardsdatascience.com/a-new-way-to-predict-probability-distributions-e7258349f464?gi=3201d118e909 A New Way to Predict Probability DistributionsExploring multi-quantile regression with CatboostHarrison HoffmanFeb 14 “Until recently, the main disadvantage of quantile regression was that one model had to be trained
What I Read: Convolutions, Probability
https://www.countbayesie.com/blog/2022/11/30/understanding-convolutions-in-probability-a-mad-science-perspective Understanding Convolutions in Probability: A Mad-Science PerspectiveWill Kurt, Count BayesieDecember 01, 2022 “If you’ve ever done much mad science you’ll know that a major problem is selectively determining the