Advanced topics
4 articles
- Maintaining Feature Balance in Machine Learning ModelsFeature or column importance in ML models gauges predictor significance.
- Understanding Explainability & Prediction DetailsEntity-level explainability is a great tool for understanding and interpreting ML models, improving them and even help finding errors.
- SHAP valuesSHAP values quantify feature impact in ML models, revealing key drivers in predictions and aiding in data-driven decision-making.
- Model performance metrics for binary modelsLearn about binary model metrics: Base Rate, Precision, Detection, AUC, LogLoss guide accurate, balanced predictions for distinct classes.