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:

----------------
Arguments
----------------

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
----------------

outputRegressor: <outputFile>
    Output regressor