Fit MaxAbsScaler

Scale each feature by its maximum absolute value. This estimator scales and translates each feature individually such that the maximal absolute value of each feature in the training set will be 1.0.

Parameters

Transformer [string]

Scikit-learn python code. See MaxAbsScaler for information on different parameters.

Default:

from sklearn.preprocessing import MaxAbsScaler

transformer = MaxAbsScaler()

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:FitMaxabsscaler:

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

transformer: Transformer
    Default value:  from sklearn.preprocessing import MaxAbsScaler

transformer = MaxAbsScaler()
    Argument type:  string
    Acceptable values:
            - String value
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
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

----------------
Outputs
----------------

outputTransformer: <outputFile>
    Output transformer