Fit XGBRFRegressorΒΆ
Implementation of the scikit-learn API for XGBoost random forest regression.
Parameters
- Regressor [string]
Scikit-learn python code. See XGBRFRegressor for information on different parameters.
Default:
from xgboost import XGBRFRegressor regressor = XGBRFRegressor(n_estimators=100)
- Training dataset [file]
- Training dataset pickle file used for fitting the classifier. If not specified, an unfitted classifier is created.
Outputs
- Output regressor [fileDestination]
- Pickle file destination.
Command-line usage
>qgis_process help enmapbox:FitXgbrfregressor
:
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Arguments
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regressor: Regressor
Default value: from xgboost import XGBRFRegressor
regressor = XGBRFRegressor(n_estimators=100)
Argument type: string
Acceptable values:
- String value
dataset: Training dataset (optional)
Argument type: file
Acceptable values:
- Path to a file
outputRegressor: Output regressor
Argument type: fileDestination
Acceptable values:
- Path for new file
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Outputs
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outputRegressor: <outputFile>
Output regressor