Numbers and Code

Statistics, Data Science and Programming

  • Blog
  • Learn Data Science
  • Books
  • About
  • Disclaimer
  • Blog
  • Learn Data Science
  • Books
  • About
  • Disclaimer

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

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
Developed by Think Up Themes Ltd. Powered by WordPress.