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MLS-C01 · Question #117
A Machine Learning Specialist is assigned to a Fraud Detection team and must tune an XGBoost model, which is working appropriately for test data. However, with unknown data, it is not working as expec
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Modeling
Question
A Machine Learning Specialist is assigned to a Fraud Detection team and must tune an XGBoost model, which is working appropriately for test data. However, with unknown data, it is not working as expected. The existing parameters are provided as follows. Which parameter tuning guidelines should the Specialist follow to avoid overfitting?
Exhibit
Options
- AIncrease the max_depth parameter value.
- BLower the max_depth parameter value.
- CUpdate the objective to binary:logistic.
- DLower the min_child_weight parameter value.
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Topics
#XGBoost#Overfitting#Hyperparameter Tuning#Regularization