update2
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- **Why**: Avoid blind reweighting and find the specific features causing KS to stay high.
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- **Files**:
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- `example/diagnose_ks.py`
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## 2026-01-26 — Quantile transform + sigmoid bounds for continuous features
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- **Decision**: Add optional quantile normalization (TabDDPM-style) and sigmoid-based bounds to reduce KS spikes.
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- **Why**: KS failures are dominated by boundary pile-up and tail mismatch.
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- **Files**:
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- `example/data_utils.py`
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- `example/prepare_data.py`
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- `example/export_samples.py`
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- `example/config.json`
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