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fix: Add complete LightGBM implementation (create_points, predict_score)
Critical fixes that were missing from squash merge: - Implement create_points() with use_base_score parameter - Implement predict_score() and predict_scores() - Fix leaf ID mapping bug (extract actual ID from node_index) - Add base score normalization for balanced tree contributions - Update tests and examples with score visualization This completes the 0.2.7rc1 release.
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examples/catboost-getting-started.ipynb

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"source": [
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"# <span style=\"font-family: Arial, sans-serif; color:#97f788\">xbooster</span>\n",
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"\n",
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"## <span style=\"font-family: Arial, sans-serif; color:navyblue\">CatBoost - Getting started</span>\n",
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"<span style=\"font-family: Arial, sans-serif; color:navyblue\">Repo: <a href=\"https://github.com/xRiskLab/xBooster\" title=\"GitHub link\">https://github.com/xRiskLab/xBooster</a></span>"
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"<span style=\"font-family: Arial, sans-serif; color:navyblue\">Repo: <a href=\"https://github.com/xRiskLab/xBooster\" title=\"GitHub link\">https://github.com/xRiskLab/xBooster</a></span>\n"
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Compare performance of scores"
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"### Compare performance of scores\n"
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"cell_type": "markdown",
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"metadata": {},
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"### Plot feature importance"
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"### Plot feature importance\n"
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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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"display_name": ".venv (3.10.16)",
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"language": "python",
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"name": "python3"
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examples/lightgbm-getting-started.ipynb

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