Fit AffinityPropagation

Perform Affinity Propagation Clustering.

Affinity Propagation creates clusters by identifying exemplars that best capture the data’s structure. It adapts to the data’s inherent similarities and differences and does not require a pre-specified number of clusters, making it useful for discovering clusters with varying sizes and shapes.

Usage:

  1. Open the algorithm from the processing toolbox.

  2. Load an existing training dataset or create one by clicking the processing algorithm icon, then click run.

    usr_section/usr_manual/processing_algorithms/clustering/source/usr_section/usr_manual/processing_algorithms_includes/clustering/img/affinityprop_interface.png

Parameters

Clusterer [string]

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

Default:

from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.cluster import AffinityPropagation

affinityPropagation = AffinityPropagation()
clusterer = make_pipeline(StandardScaler(), affinityPropagation)
Training dataset [file]

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

Outputs

Output clusterer [fileDestination]

Pickle file destination.

Command-line usage

>qgis_process help enmapbox:FitAffinitypropagation:

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

clusterer: Clusterer
    Default value:  from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.cluster import AffinityPropagation

affinityPropagation = AffinityPropagation()
clusterer = make_pipeline(StandardScaler(), affinityPropagation)
    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
    Argument type:  file
    Acceptable values:
            - Path to a file
outputClusterer: Output clusterer
    Argument type:  fileDestination
    Acceptable values:
            - Path for new file

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

outputClusterer: <outputFile>
    Output clusterer