Regression workflow
The regression workflow combines regressor fitting and map prediction.Optionally, the cross-validation performance of the regressor can be assessed.
Usage:
Start the algorithm from the Processing Toolbox panel.
Select a training dataset or create one by clicking the processing algorithm icon. Select a regressor and adjust its parameterization accordingly, then click run.
Live Demonstration
Parameters
- Training dataset [file]
Training dataset pickle file used for fitting the regressor.
- Regressor [string]
Scikit-Learn Python code specifying a regressor.
- Raster layer with features [raster]
A raster layer used for prediction.
- Match regressor features and raster bands by name [boolean]
Whether to match raster bands and regressor features by name.
Default: False
- Number of cross-validation folds [number]
The number of folds used for assessing cross-validation performance. Will be ignored, if the cross-validation performance assessment is skipped.
Default: 10
- Open output cross-validation regressor performance report in webbrowser after running algorithm [boolean]
Whether to open the cross-validation performance report in the web browser. Will be ignored, if the cross-validation performance assessment is skipped.
Default: True
Outputs
- Output cross-validation regressor performance report [fileDestination]
Output cross-validation performance report file destination.
- Output regressor [fileDestination]
Pickle file destination.
- Output regression layer [rasterDestination]
Predicted map file destination.
Command-line usage
>qgis_process help enmapbox:RegressionWorkflow
:
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Arguments
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dataset: Training dataset
Argument type: file
Acceptable values:
- Path to a file
regressor: Regressor
Argument type: string
Acceptable values:
- String value
- field:FIELD_NAME to use a data defined value taken from the FIELD_NAME field
- expression:SOME EXPRESSION to use a data defined value calculated using a custom QGIS expression
raster: Raster layer with features (optional)
Argument type: raster
Acceptable values:
- Path to a raster layer
matchByName: Match regressor features and raster bands by name (optional)
Default value: false
Argument type: boolean
Acceptable values:
- 1 for true/yes
- 0 for false/no
- field:FIELD_NAME to use a data defined value taken from the FIELD_NAME field
- expression:SOME EXPRESSION to use a data defined value calculated using a custom QGIS expression
nfold: Number of cross-validation folds (optional)
Default value: 10
Argument type: number
Acceptable values:
- A numeric value
- field:FIELD_NAME to use a data defined value taken from the FIELD_NAME field
- expression:SOME EXPRESSION to use a data defined value calculated using a custom QGIS expression
openReport: Open output cross-validation regressor performance report in webbrowser after running algorithm
Default value: true
Argument type: boolean
Acceptable values:
- 1 for true/yes
- 0 for false/no
- field:FIELD_NAME to use a data defined value taken from the FIELD_NAME field
- expression:SOME EXPRESSION to use a data defined value calculated using a custom QGIS expression
outputRegressorPerformance: Output cross-validation regressor performance report (optional)
Argument type: fileDestination
Acceptable values:
- Path for new file
outputRegressor: Output regressor
Argument type: fileDestination
Acceptable values:
- Path for new file
outputRegression: Output regression layer (optional)
Argument type: rasterDestination
Acceptable values:
- Path for new raster layer
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Outputs
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outputRegressorPerformance: <outputHtml>
Output cross-validation regressor performance report
outputRegressor: <outputFile>
Output regressor
outputRegression: <outputRaster>
Output regression layer