mlflow--mlflow
wehub-resource-sync
28 行
617 B
Markdown
28 行
617 B
Markdown
# XGBoost Example
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This example trains an XGBoost classifier with the iris dataset and logs hyperparameters, metrics, and trained model.
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## Running the code
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```
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python train.py --learning-rate 0.2 --colsample-bytree 0.8 --subsample 0.9
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```
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You can try experimenting with different parameter values like:
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```
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python train.py --learning-rate 0.4 --colsample-bytree 0.7 --subsample 0.8
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```
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Then you can open the MLflow UI to track the experiments and compare your runs via:
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```
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mlflow server
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```
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## Running the code as a project
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```
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mlflow run . -P learning_rate=0.2 -P colsample_bytree=0.8 -P subsample=0.9
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```
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