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I ran 580 experiments (yes, 580 🤯) to check if we can quantify data drift's impact on model performance using only drift metrics.
I ran 580 experiments (yes, 580 🤯) to check if we can quantify data drift's impact on model performance using only drift metrics.
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For these experiments, I built a technique that relies on drift signals to estimate model performance. I compared its results against the current SoTA performance estimation methods and checked which technique performs best.
For these experiments, I built a technique that relies on drift signals to estimate model performance. I compared its results against the current SoTA performance estimation methods and checked which technique performs best.
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The plot below summarizes the general results. It measures the quality of performance estimation versus the absolute performance change. (The lower, the better).
The plot below summarizes the general results. It measures the quality of performance estimation versus the absolute performance change. (The lower, the better).
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Full experiment: 
Full experiment: 
link
https://www.nannyml.com/blog/data-drift-estimate-model-performance
https://www.nannyml.com/blog/data-drift-estimate-model-performance
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In it, I describe the setup, datasets, models, benchmarking methods, and the code used in the project.
In it, I describe the setup, datasets, models, benchmarking methods, and the code used in the project.
I ran 580 experiments (yes, 580 🤯) to check if we can quantify data drift's impact on model performance using only drift metrics.

For these experiments, I built a technique that relies on drift signals to estimate model performance. I compared its results against the current SoTA performance estimation methods and checked which technique performs best.

The plot below summarizes the general results. It measures the quality of performance estimation versus the absolute performance change. (The lower, the better).

Full experiment: https://www.nannyml.com/blog/data-drift-estimate-model-performance

In it, I describe the setup, datasets, models, benchmarking methods, and the code used in the project.
🔥
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