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, 2018SaremAlgorithms, Hilbert Spaces, Linear Model, MARS, Python

Another simple time-series model – using Naive-Bayes for forecasting August 2, 2018Sarem1 CommentClassification, Forecasting, Naive Bayes, Time Series, Uncategorized

Building a strong time-series forecasting model with simple indicator functions July 24, 2018Sarem2 CommentsAlgorithms, Applications, Forecasting, Python, Time Series

A partially interpretable, semi-parametric Neural Network April 9, 2018SaremAlgorithms, Applications, Machine Learning, Neural Networks, Python, Uncategorized

A brief proof-of-concept for Kernelized Decision Trees March 22, 2018SaremApplications, Classification, Decision Trees, Machine Learning, Python

How Decision Trees can learn non-rectangular decision splits March 18, 2018SaremClassification, Decision Trees, Machine Learning, Python

RuleFit on real-world data March 10, 2018Sarem1 CommentAlgorithms, Applications, Decision Trees, Gradient Boosting, Machine Learning, Python

RuleFit for interpretable Machine Learning March 10, 2018Sarem3 CommentsAlgorithms, Decision Trees, Machine Learning, Python, Random Forest