How to maintain Model Effectiveness after deployed

added 18.05.2020 18:03

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A good model will have high accuracy for positive data at the same time it should give a low score for negative ingested data.

Based on business objective, from recent model results, get the accuracy score on positive data, and negative data, and get reconstruction error value from the AE model.

Let us see the possible actions we can take related to model effectiveness Actions 1: Retrain the model with new data When the model produced high accuracy score and negative test accuracy is also significantly high, get the reconstruction error value from the AE model with recent data.

When the model produced a low accuracy score on recent positive data and negative test accuracy is significantly high.

Furthermore, the reconstruction error value is also high for recent input data is a clear indication that the new recent input data is much different and has new features than the model originally trained.