As regular readers of this blog know, I’ve migrated to a weekly (or potentially longer) topic focus, and this week’s topic is variable selection. And the next planned post in the series will compare and contrast ridge regression and the LASSO (least absolute shrinkage and selection operator). There also are some new results for the … Continue reading The Tibshirani’s – Statistics and Machine Learning Superstars
The LASSO (Least Absolute Shrinkage and Selection Operator) is a method of automatic variable selection which can be used to select predictors X* of a target variable Y from a larger set of potential or candidate predictors X. Developed in 1996 by Tibshirani, the LASSO formulates curve fitting as a quadratic programming problem, where the … Continue reading Variable Selection Procedures – The LASSO
More than 25,000 visited businessforecastblog, March 2012-December 2013, some spending hours on the site. Interest ran nearly 200 visitors a day in December, before my ability to post was blocked by a software glitch, and we did this re-boot. Now I have hundreds of posts offline, pertaining to several themes, discussed below. How to put this material … Continue reading The On-Coming Tsunami of Data Analytics
Over the Holidays – while frustrated in posting by a software glitch – I looked at the whole “shallow data issue” in light of a new technique I’ve learned called bagging. Bottom line, using spreadsheet simulations, I can show bagging radically reduces out-of-sample forecast error, in a situation typical for a lot business forecasting – where there … Continue reading Forecasting in Data-limited Situations – A New Day
