Examples of stallone.cluster.RegularSpatialClustering

stallone.cluster.RegularSpatialClustering
Clusters data objects in such a way, that cluster centers are at least in distance of dmin to eachother according to the given metric. The assignment of data objects to cluster centers is performed by Voronoi paritioning. That means, that a data object is assigned to that clusters center, which has the least distance. @param < T> data (whatever kind) to cluster @author Martin Senne






    public IClustering regspace(IDataInput data, IMetric<IDoubleArray> metric, double dmin)
    {
        RegularSpatialClustering clustering = new RegularSpatialClustering();
        clustering.setDmin(dmin);
        clustering.setMetric(metric);
        clustering.setInput(data);
        return (clustering);
    }

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Related Classes of stallone.cluster.RegularSpatialClustering

stallone.api.cluster.ClusterFactory

stallone.api.doubles.IDoubleArray

stallone.datasequence.DataList

stallone.discretization.VoronoiDiscretization

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