Comparison of XGBoost hyperparameter tuning optimization results.

Comparison of XGBoost hyperparameter tuning optimization results.

<p>Comparison of XGBoost hyperparameter tuning optimization results.</p>

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Bibliographic Details
Main Author:	Wenguang Li (6528113) (author)
Other Authors:	Yan Peng (104995) (author), Ke Peng (2220973) (author)
Published:	2024
Subjects:	Science Policy Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified body mass index stacking model based performing lightgbm model model &# 8217 layer stacking model data balance processing random forest model model integration strategies xlink "> diabetes xgboost model optimized model integration xgboost model random oversampling data imbalance significant impact scientific basis results show research object reaching effects publicly available powerful tool particularly crucial new idea kaggle platform genetic algorithm early intervention early diagnosis also provides also provided
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Summary:	<p>Comparison of XGBoost hyperparameter tuning optimization results.</p>

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