Published inTowards Data ScienceNon-Linearity: Can Linear Regression Compete With Gradient Boosting?Linear models can handle non-linear relationships thanks to data pre-processing. But how close can they get to more sophisticated models?Oct 119Oct 119

Published inTowards Data ScienceCausality in ML Models: Introducing Monotonic ConstraintsMonotonic constraints are key to making machine learning models actionable, yet they are still quite unusedSep 612Sep 612

Published inTowards Data ScienceWhat’s Wrong With R-Squared (And How to Fix It)Even if you think you are using R-Squared out-of-sample, you are not. Here is whyAug 719Aug 719

Published inTowards Data ScienceForget Statistical Tests: A/B Testing Is All About SimulationsHow simulations outperform traditional stats in that they are easier to understand, more flexible, and economically meaningfulJul 414Jul 414

Published inTowards Data ScienceHypothesis Testing Explained (How I Wish It Was Explained to Me)Most resources focus on things like Confidence and Power. But they don’t really matter: here is what you should care aboutMay 136May 136

Published inTowards Data ScienceWhy You Should Never Use Cross-ValidationIn real-world applications, using randomized cross-validation is always a bad choice. Here is why.Mar 2741Mar 2741

Published inTowards Data ScienceAre Outliers Harder To Predict?An empirical analysis about whether ML models make more mistakes when making predictions on outliersFeb 411Feb 411

Published inTowards Data Science“Approximate-Predictions” Make Feature Selection Radically FasterFeature selection is so slow because it requires the creation of many models. Find out how to make it blazingly faster thanks to…Nov 17, 202323Nov 17, 202323

Published inTowards Data ScienceYour Dataset Has Missing Values? Do Nothing!Models can handle missing values out-of-the-box more effectively than imputation methods. An empirical proofOct 9, 20237Oct 9, 20237

Published inTowards Data ScienceWhich Features Are Harmful For Your Classification Model?How to calculate the Error Contribution of the features of a classifier, with the goal of understanding and improving the modelSep 12, 202312Sep 12, 202312