Bayesian harmonic regression and a poor man’s spike-and-slab prior December 1, 2020SaremBayesian Methods, Forecasting, Julia, Time Series, Uncertainty

Why probability and uncertainty should be an integral part of regression models (II) October 9, 2020SaremJulia, Linear Model, Machine Learning, Probability, Regression, Statistics, Uncertainty

Why probability and uncertainty should be an integral part of regression models (I) June 26, 2020SaremJulia, Regression, Statistics, Uncertainty

Some interesting observations with Distance Correlation coefficients May 15, 2020Sarem2 CommentsData Analysis, Feature Selection, Julia

A brief, probabilistic demand forecast model May 7, 2020SaremAlgorithms, Applications, Forecasting, Julia, Machine Learning, Time Series

Generalized Additive Neural Networks December 17, 2019Sarem2 CommentsInterpretable Machine Learning, Julia, Linear Model, Machine Learning, Neural Networks

Some experiments with Local Linear Regression. Part I – A primer on Local Linear Regression November 30, 2019SaremAlgorithms, Interpretable Machine Learning, Linear Model

More simple time-series models – this time with Decision Trees February 24, 2019SaremApplications, Decision Trees, Forecasting, Machine Learning, Time Series

Interpretable, scalable, non-linear – can we have it all? An approach with K-Means October 3, 2018SaremAlgorithms, Applications, Decision Trees, Python, Random Forest, Uncategorized

Non-Greedy MARS regression September 11, 2018Sarem2 CommentsAlgorithms, Hilbert Spaces, Linear Model, MARS, Python