Fit MinMaxScaler
Transform features by scaling each feature to a given range. This estimator scales and translates each feature individually such that it is in the given range on the training set, e.g. between zero and one.
Usage:
Start the algorithm from the Processing Toolbox panel.
Select a raster layer to process and click run.
Parameters
- Transformer [string]
Scikit-learn python code. See MinMaxScaler for information on different parameters. Default:
from sklearn.preprocessing import MinMaxScaler transformer = MinMaxScaler\(feature_range=\(0, 1\), clip=False\)
- Raster layer with features [raster]
Raster layer with feature data X used for fitting the transformer. Mutually exclusive with parameter: Training dataset
- Sample size [number]
Approximate number of samples drawn from raster. If 0, whole raster will be used. Note that this is only a hint for limiting the number of rows and columns. Default: 1000
- Training dataset [file]
Training dataset pickle file used for fitting the transformer. Mutually exclusive with parameter: Raster layer with features
Outputs
- Output transformer [fileDestination]
Pickle file destination.
Command-line usage
>qgis_process help enmapbox:FitMinmaxscaler
:
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Arguments
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transformer: Transformer
Default value: from sklearn.preprocessing import MinMaxScaler
transformer = MinMaxScaler(feature_range=(0, 1), clip=False)
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
featureRaster: Raster layer with features (optional)
Argument type: raster
Acceptable values:
- Path to a raster layer
sampleSize: Sample size (optional)
Default value: 1000
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
dataset: Training dataset (optional)
Argument type: file
Acceptable values:
- Path to a file
outputTransformer: Output transformer
Argument type: fileDestination
Acceptable values:
- Path for new file
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Outputs
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outputTransformer: <outputFile>
Output transformer