Fit LGBMClassifier

Implementation of the scikit-learn API for LightGBM classifier.

Usage:

1. Start the algorithm from the Processing Toolbox panel.

2. Select a training dataset or create one by clicking the processing algorithm icon, then click run.

   

Parameters

Classifier [string]

Scikit-learn python code. See LGBMClassifier for information on different parameters. Default:

from lightgbm import LGBMClassifier
classifier = LGBMClassifier\(n_estimators=100\)

Training dataset [file]

Training dataset pickle file used for fitting the classifier. If not specified, an unfitted classifier is created.

Outputs

Output classifier [fileDestination]

Pickle file destination.

Command-line usage

>qgis_process help enmapbox:FitLgbmclassifier:

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

classifier: Classifier
    Default value:    from lightgbm import LGBMClassifier
classifier = LGBMClassifier(n_estimators=100)
    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
dataset: Training dataset (optional)
    Argument type:    file
    Acceptable values:
        - Path to a file
outputClassifier: Output classifier
    Argument type:    fileDestination
    Acceptable values:
        - Path for new file

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

outputClassifier: <outputFile>
    Output classifier