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      "end_summary": "I have successfully implemented all the requested code cleanup improvements for the ClusterBasedNormalizer class in rdt/transformers/numerical.py:\n\n1. **Clarified inputs and outputs in the docstring** - Expanded the class docstring with detailed explanation of inputs, outputs, and transformation process\n2. **Described purpose of STD_MULTIPLIER** - Added explanatory comment about how the value 4 ensures ~95% of values fall within [-1,1] range\n3. **Removed n_init parameter** - Eliminated the explicit n_init=1 parameter from BayesianGaussianMixture constructor since it's the default in sklearn\n4. **Explained warnings.simplefilter('ignore')** - Added comment clarifying it avoids convergence warnings during BGMM fitting\n5. **Switch order of operations in transformation** - Completely rewrote _transform method to first select components based on probabilities, then normalize the selected component values\n6. **Removed both noqa's** - Eliminated the two `# noqa: PD013` comments\n7. **Reverse transform handling** - Kept the proper if/else structure (since the original was correct) but ensured it works correctly with indexing\n8. **Maintained existing astype/round/clip logic** - Confirmed that parent class already handles rounding and clipping properly before astype call\n\nAll tests pass, including the specific test mentioned in the specification (TestClusterBasedNormalizer::test__fit), and the baseline failure regarding the n_init parameter has been resolved.",
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