The following really made my day. I tell every data scientist I know about vtreat and urge them to read the paper. Jason Wolosonovich Jason, thanks for your support and thank you so much for taking the time to say this (and for your permission to quote you on this). For those interested the R … Continue reading A Kind Note That We Really Appreciate
Category: vtreat
Big News: Porting vtreat to Python
We at Win-Vector LLC have some big news. We are finally porting a streamlined version of our R vtreat variable preparation package to Python. vtreat is a great system for preparing messy data for suprevised machine learning. The new implementation is based on Pandas, and we are experimenting with pushing the sklearn.pipeline.Pipeline APIs to their … Continue reading Big News: Porting vtreat to Python
Big News: Porting vtreat to Python
We at Win-Vector LLC have some big news. We are finally porting a streamlined version of our R vtreat variable preparation package to Python. vtreat is a great system for preparing messy data for suprevised machine learning. The new implementation is based on Pandas, and we are experimenting with pushing the sklearn.pipeline.Pipeline APIs to their … Continue reading Big News: Porting vtreat to Python
vtreat Variable Importance
vtreat‘s purpose is to produce pure numeric R data.frames that are ready for supervised predictive modeling (predicting a value from other values). By ready we mean: a purely numeric data frame with no missing values and a reasonable number of columns (missing-values re-encoded with indicators, and high-degree categorical re-encode by effects codes or impact codes). … Continue reading vtreat Variable Importance
Sharing Modeling Pipelines in R
Reusable modeling pipelines are a practical idea that gets re-developed many times in many contexts. wrapr supplies a particularly powerful pipeline notation, and a pipe-stage re-use system (notes here). We will demonstrate this with the vtreat data preparation system. Our example task is to fit a model on some arbitrary data. Our model will try … Continue reading Sharing Modeling Pipelines in R