Hierarchical feature clustering

Evaluate feature multicollinearity by performing hierarchical/agglomerative clustering with Ward linkage using squared Spearman rank-order correlation as distance between features. The result report includes i) pairwise squared Spearman rank-order correlation matrix, ii) clustering dendrogram, iii) inter-cluster correlation distribution, iv) intra-cluster correlation distribution, and v) a clustering hierarchy table detailing selected cluster representatives for each cluster size n. For further analysis, all relevant results are also stored as a JSON sidecar file next to the report.

Parameters

Dataset [file]

Dataset pickle file with feature data X to be evaluated.

Do not report plots [boolean]

Skip the creation of plots, which can take a lot of time for large features sets.

Default: False

Open output report in webbrowser after running algorithm [boolean]

Whether to open the output report in the web browser.

Default: True

Outputs

Output report [fileDestination]

Report file destination.

Command-line usage

>qgis_process help enmapbox:HierarchicalFeatureClustering:

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Arguments
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dataset: Dataset
    Argument type:  file
    Acceptable values:
            - Path to a file
noPlot: Do not report plots
    Default value:  false
    Argument type:  boolean
    Acceptable values:
            - 1 for true/yes
            - 0 for false/no
openReport: Open output report in webbrowser after running algorithm
    Default value:  true
    Argument type:  boolean
    Acceptable values:
            - 1 for true/yes
            - 0 for false/no
outputHierarchicalFeatureClustering: Output report
    Argument type:  fileDestination
    Acceptable values:
            - Path for new file

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Outputs
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outputHierarchicalFeatureClustering: <outputHtml>
    Output report