Cross-Posting: One Metric to Fool Yourself - A Cautionary Tale
Details
When fitting a model, statistical or machine learning, we often want to evaluate its performance. We have a wealth of different methods for all types of scenarios, from classification and regression to survival analysis. While these performance metrics work as intended, we can often get more out of models by carefully combining and using these metrics to capture what we really care about in our models. Optimal performance and minimal bias.
Register for this event at the R Meetup - Real Data Science USA
https://www.meetup.com/real-data-science-usa-r-meetup/
AI summary
By Meetup
Talk for statisticians and ML practitioners at an R Meetup on combining metrics to reduce bias in model evaluation.
AI summary
By Meetup
Talk for statisticians and ML practitioners at an R Meetup on combining metrics to reduce bias in model evaluation.