New vtreat Documentation (Starting with Multinomial Classification)

This article was first published on python – Win-Vector Blog , and kindly contributed to python-bloggers. (You can report issue about the content on this page here)
Want to share your content on python-bloggers? click here.

Nina Zumel finished some great new documentation showing how to use Python vtreat to prepare data for multinomial classification mode. And I have finally finished porting the documentation to R vtreat. So we now have good introductions on how to use vtreat to prepare data for the common tasks of:

That is now 8 introductions to start with. To use vtreat you only have to work through one introduction (the one helping with the task you have at hand in the language you are using).

As I have said before:

  • vtreat helps with project blocking issues commonly seen in real world data: missing values, re-coding categorical variables, and dealing high cardinality categorical variables.
  • If you aren’t using a tool like vtreat in your data science projects: you are really missing out (and making more work for yourself).
To leave a comment for the author, please follow the link and comment on their blog: python – Win-Vector Blog .

Want to share your content on python-bloggers? click here.