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
