PinnedInData Science CollectivebyBradley Stephen Shaw·Apr 4, 2025Teach Your GBM to Extrapolate with Model StackingBackgroundA response icon6A response icon6
InPython in Plain EnglishbyBradley Stephen Shaw·Mar 11, 2025Do Opposites Attract? A Data Science Love StoryIs combining gradient-boosted trees with linear models a silver bullet for extrapolation or a memory-hungry nightmare?A response icon1A response icon1
InPython in Plain EnglishbyBradley Stephen Shaw·Feb 10, 2025A Cautionary Tale: Why You Might Want to Calibrate Your GBM ModelsA real-world example of some of the dangers lurking below the surface of a “good” GBM model.A response icon3A response icon3
InTDS ArchivebyBradley Stephen Shaw·Apr 5, 2024How Reliable Are Your Time Series Forecasts, Really?How cross-validation, visualisation, and statistical hypothesis testing combine to reveal the optimal forecasting horizonA response icon7A response icon7
InPython in Plain EnglishbyBradley Stephen Shaw·Mar 15, 2024Time series residuals: gold in them thar hillsHow model crumbs provide more insight than you might thinkA response icon1A response icon1
InTDS ArchivebyBradley Stephen Shaw·Mar 1, 2024False Prophet: Lightning Strikes TwiceInsights from incorporating external weather data into a time series regression inspired by Meta’s ProphetA response icon1A response icon1
InTDS ArchivebyBradley Stephen Shaw·Jan 13, 2024Hybrid Models for Time Series RegressionUsing multiple model forms to capture and forecast the components of complex time seriesA response icon1A response icon1
InTDS ArchivebyBradley Stephen Shaw·Nov 25, 2023False Prophet: Comparing a Regression Model to Meta’s ProphetCan my Frankenstein of a time series regression model — inspired by Prophet — compete with the real deal?A response icon1A response icon1
InTDS ArchivebyBradley Stephen Shaw·Oct 31, 2023False Prophet: a Homemade Time Series Regression ModelBorrowing ideas from Meta’s Prophet to build a powerful time series regression modelA response icon5A response icon5