Nina Zumel finished new documentation on how vtreat‘s cross validation works, which I want to share here.

vtreat is a system that makes data preparation for machine learning a “one-liner” (available in R or available in Python). We have a set of starting off points here. These documents describe what vtreat does for you, you just find the one that matches your task and you should have a good start for solving data science problems in R or in Python.

The latest documentation is a bit about how vtreat works, and how to control some of the details of the work it is doing for you.

The new documentation is:

• Custom cross validation plans in Python.
• Custom cross validation plans in R.

Please give one of the examples a try, and consider adding vtreat to your data science workflow.

Categories: Administrativia Pragmatic Data Science

Tagged as: data science Machine Learning Practical Data Science Pragmatic Machine Learning pydata python R

jmount

Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.