Enhance training analysis page with test metrics and confusion matrix

- Added a section to display test metrics for model performance on the held-out test set.
- Implemented confusion matrix visualization to analyze prediction breakdown.
- Refactored sidebar settings to streamline metric selection and improve user experience.
- Updated cross-validation statistics to compare CV performance with test metrics.
- Enhanced DatasetEnsemble methods to handle empty data scenarios gracefully.
- Introduced debug scripts to assist in identifying feature mismatches and validating dataset preparation.
- Added comprehensive tests for DatasetEnsemble to ensure feature consistency and correct behavior across various scenarios.

pyproject.toml

@@ -66,7 +66,7 @@ dependencies = [
     "pypalettes>=0.2.1,<0.3",
     "ty>=0.0.2,<0.0.3",
     "ruff>=0.14.9,<0.15",
-    "pandas-stubs>=2.3.3.251201,<3",
+    "pandas-stubs>=2.3.3.251201,<3", "pytest>=9.0.2,<10",
 ]
 
 [project.scripts]