eurybia
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MAIF
⚓ Eurybia monitors model drift over time and securizes model deployment with data validation
The baseline and current datasets colors are not always consistent from variable to variable (e.g. current dataset is blue for var 1, then brown for var 2)
**Description of Problem**: Eurybia is currently designed to detect drift on data built in batch mode. If deployed model consumes and does the data preparation in API mode, we have...
**Description of Problem**: Data drift is not necessarily sufficient to explain evolution of performance of deployed model. The concept drift would complete the explanation of the evolution of performance. And...
**Description of Problem**: In the current implementation of the Smart Drift reports, all data points are visualized without any filtering options. This leads to cluttered and sometimes overwhelming visualizations, making...
What existing problem does the pull request solve? The pull request introduces a filtering feature to the compile function of the Smart Drift object. Previously, users experienced cluttered visualizations due...
I have columns that are excluded from the analysis because the types are different. Floats and int. In the report, these columns end up in the "Ignored columns in the...
**Description of Problem**: I was surprised to find some features with missing values at the bottom of the feature importance list. It was important for my use case to spot...
In report HTML in Univariate analysis, when you select a column to analyse your result, the box (dash line) come back to the first column. This can cause a misunderstanding...
# Description Fixes #57 I made datapane a submodule of eurybia.report. Following dependencies have been added to make it work: ```python "altair>=5.0.0", "pyarrow>=9.0.0", "chardet>=5.0.0,=4.7.1,=0.5.3", "dominate>=2.7.0,=1.9.0,=0.16.7", ``` I had to change...
**Description of Problem**: Due to datapane support being dropped, Eurybia is stuck with pandas= 2. **Examples**: **Blockers**: **Definition of Done**: Eurybia works properly along pandas>=2 in the same virtualenv.