Chapter 9: Model Evaluation Metrics
Individual Conditional Expectation (ICE) Plots
Overview
Model evaluation is essential for determining the accuracy and effectiveness of your model. Evaluation metrics can help a data scientist develop a robust model on the training and validation data sets while also providing a framework to evaluate the accuracy of the final model by applying these metrics to the hold-out test and out-of-time data sets. A data scientist must select the appropriate ...
Get End-to-End Data Science with SAS now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.