Fit GaussianProcessRegressor
Gaussian process regression (GPR).
Parameters
- Regressor [string]
Scikit-learn python code. See GaussianProcessRegressor for information on different parameters.
Default:
from sklearn.pipeline import make_pipeline from sklearn.preprocessing import StandardScaler from sklearn.gaussian_process import GaussianProcessRegressor from sklearn.gaussian_process.kernels import RBF gpr = GaussianProcessRegressor(RBF()) regressor = make_pipeline(StandardScaler(), gpr)
- 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:FitGaussianprocessregressor
:
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Arguments
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regressor: Regressor
Default value: from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn.gaussian_process.kernels import RBF
gpr = GaussianProcessRegressor(RBF())
regressor = make_pipeline(StandardScaler(), gpr)
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