Machine Learning
Choosing Evaluation Metrics: Precision, Recall, ROC, and Calibration
A practitioner's guide to picking the right evaluation metric for a classification problem, and why a well-ranked model can still be badly calibrated.
3 min read
Tag
Model Evaluation
4 articles
Machine Learning
Class Imbalance: Sampling, Weights, and the Right Metrics
Practical techniques for imbalanced classification, and why accuracy is the wrong number to optimize when the positive class is 2% of your data.
3 min read
Machine Learning
Train/Validation/Test Splits Done Right (Including Time Series)
Random splits are wrong more often than practitioners assume — a walkthrough of when to use them and when time-based or grouped splits are required.
3 min read
Machine Learning
Data Leakage: The Silent Model Killer
Data leakage produces models that look excellent in validation and fail in production. Here's how it sneaks in and the checks that catch it early.
3 min read