The Microsoft Data Science User Group just sponsored Dr. Nina Zumel‘s presentation “Preparing Data for Analysis Using R”. Microsoft saw Win-Vector LLC‘s ODSC West 2015 presentation “Prepping Data for Analysis using R” and generously offered to sponsor improving it and disseminating it to a wider audience. We feel Nina really hit the ball out of … Continue reading More on preparing data
Nina and I are proud to share our lecture: “Prepping Data for Analysis using R” from ODSC West 2015. Nina Zumel and John Mount ODSC WEST 2015 It is about 90 minutes, and covers a lot of the theory behind the vtreat data preparation library. We also have a Github repository including all the lecture … Continue reading Prepping Data for Analysis using R
Nina Zumel and I are proud to announce our R vtreat variable treatment library has just been accepted by CRAN! It will take some time for the vtreat package to progress to various CRAN mirrors, but as of now you can install vtreat with the command: install.packages('vtreat', repos='http://cran.r-project.org/') Instead of needing to use devtools to … Continue reading vtreat up on CRAN!
The Win-Vector LLC vtreat library is a library we supply (under a GPL license) for automating the simple domain independent part of variable cleaning an preparation. The idea is you supply (in R) an example general data.frame to vtreat’s designTr...
When you apply machine learning algorithms on a regular basis, on a wide variety of data sets, you find that certain data issues come up again and again: Missing values (NA or blanks) Problematic numerical values (Inf, NaN, sentinel values like 999999999 or -1) Valid categorical levels that don’t appear in the training data (especially … Continue reading Vtreat: designing a package for variable treatment → Related posts: R minitip:…
