When Should a Machine Learning Model Be Retrained?

By datasciencecentral - 2020-12-22

Description

A few years ago, it was extremely uncommon to retrain a machine learning model with new observations systematically. This was mostly because the model retrain…

Summary

MLOps solutions have brought about this change with easy access to automation around model retraining, and often the most straightforward approach to trigger retraining is schedule-based.
The most basic, fundamental reason for model retraining is that the outside world that is being predicted keeps changing, and consequently the underlying data changes, causing model drift.
When there is high variance in the model performance, it makes sense to retrain a model with a training dataset that includes new observations and increases its size.

Topics

Backend (0.23)
Machine_Learning (0.19)
NLP (0.13)

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