What is the typical taxonomy for clustering methods? What is the typical taxonomy for clustering methods?
For example, for regression we can talk about: simple regression, multiple univariate regression, and multivariate regression. And then, we can divide each of those three branches in two sub-branches: linear and non-linear.
In that sense, I need a taxonomy for clustering methods, so I can approach them and study them in a more organized way.
Kind Regards
 A: There is a long list of clustering algorithms here: https://elki-project.github.io/algorithms/
Clustering Algorithms:

    AffinityPropagationClusteringAlgorithm
    CanopyPreClustering
    Density-based clustering:
        DBSCAN
        GeneralizedDBSCAN
        LSDBC
        GriDBSCAN
        OPTICSXi
        OPTICSHeap
        OPTICSList
        DeLiClu
        FastOPTICS
        NaiveMeanShiftClustering
    EM
    Hierarchical clustering family:
        AGNES
        SLINK
        CLINK
        AnderbergHierarchicalClustering
        SLINKHDBSCANLinearMemory
        HDBSCANLinearMemory
        Cluster extraction:
        HDBSCANHierarchyExtraction
        SimplifiedHierarchyExtraction
        ExtractFlatClusteringFromHierarchy
    K-Means family:
        KMeansSort
        KMeansCompare
        KMeansHamerly
        KMeansElkan
        KMeansLloyd
        ParallelLloydKMeans
        KMeansMacQueen
        KMediansLloyd
        KMedoidsPAM
        KMedoidsEM
        CLARA
        BestOfMultipleKMeans
        KMeansBisecting
        KMeansBatchedLloyd
        KMeansHybridLloydMacQueen
        SingleAssignmentKMeans
        XMeans
    SNNClustering
    Correlation clustering algorithms:
        CASH
        COPAC
        ERiC
        FourC
        HiCO
        LMCLUS
        ORCLUS
    Subspace (axis-parallel) clustering algorithms:
        CLIQUE
        DiSH
        DOC
        HiSC
        P3C
        PreDeCon
        PROCLUS
        SUBCLU
    Biclustering algorithms:
        ChengAndChurch
    Clustering algorithms for 1-dimensional data only:
        KNNKernelDensityMinimaClustering
    Trivial clustering algorithms (for reference and evaluation):
        ExternalClustering
        ByLabelClustering
        ByLabelHierarchicalClustering
        ByModelClustering
        TrivialAllInOne
        TrivialAllNoise
        ByLabelOrAllInOneClustering
    Uncertain clustering algorithms:
        FDBSCAN
        CKMeans
        UKMeans
        RepresentativeUncertainClustering
        CenterOfMassMetaClustering

