Causal Analysis - ML 132
Adventures in Machine Learning
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The Importance of Second Passive Analysis and Monitoring Data Sets for Model Drift
This chapter emphasizes the need to conduct a second passive analysis to evaluate problematic features in a model and the importance of reviewing predictions weeks or months later. They also discuss the concept of model drift and the necessity of monitoring data statistics to ensure feature relevance over time.
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