Feature drift is based on understanding and monitoring of changes in the statistics of the dataset the model was trained on vs the dataset statistics the model is currently predicting. As mentioned earlier, data is expected to evolve over time. Therefore, the monitoring of this data needs to be able to capture this evolution and know when the data has evolved past a certain divergence threshold or if it has simply changed completely.
ModelOps lets you capture the training dataset statistics and the feature importance. Providing this information, monitoring the online statistics relative to this becomes a metric capture and comparison process.
- Select the Feature Drift tab.The feature drift details display.
