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:

• Regression: R regression example, Python regression example.
• Classification: R classification example, Python classification example.
• Unsupervised data preparation: R unsupervised example, Python unsupervised example.
• Multinomial classification: R multinomial classification example, Python multinomial classification example.

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).