Examples of EuclideanDistance

cascading.assembly.EuclideanDistance
Computes the euclidean distance between every unique set of first fields, with using the label and value of each element.
Expects on input three values: item, label, value
com.heatonresearch.aifh.distance.EuclideanDistance
eatonresearch.com/wiki/Euclidean_Distance
org.apache.commons.math3.ml.distance.EuclideanDistance
Calculates the L₂ (Euclidean) distance between two points. @since 3.2
stallone.doubles.EuclideanDistance
@author noe

weka.core.EuclideanDistance

kipedia.org/wiki/Euclidean_distance.

BibTeX:

 @misc{missing_id, author = {Wikipedia}, title = {Euclidean distance}, URL = {http://en.wikipedia.org/wiki/Euclidean_distance} }

Valid options are:

 -D Turns off the normalization of attribute  values in distance calculation.

 -R <col1,col2-col4,...> Specifies list of columns to used in the calculation of the  distance. 'first' and 'last' are valid indices. (default: first-last)

 -V Invert matching sense of column indices.

@author Gabi Schmidberger (gabi@cs.waikato.ac.nz) @author Ashraf M. Kibriya (amk14@cs.waikato.ac.nz) @author FracPete (fracpete at waikato dot ac dot nz) @version $Revision: 1.13 $

Examples of stallone.doubles.EuclideanDistance

        return (clustering);
    }


    public IClustering kmeans(IDataInput data, int k, int maxIter)
    {
        return (kmeans(data, new EuclideanDistance(), k, maxIter));
    }

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Examples of stallone.doubles.EuclideanDistance

        return (kmeans(data, new EuclideanDistance(), k, maxIter));
    }


    public IClustering kmeans(IDataSequence data, int k, int maxIter)
    {
        return (kmeans(data, new EuclideanDistance(), k, maxIter));
    }

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Examples of stallone.doubles.EuclideanDistance

        return (kmeans(data, new EuclideanDistance(), k, maxIter));
    }


    public IClustering kmeans(IDataInput data, int k)
    {
        return (kmeans(data, new EuclideanDistance(), k, 1000));
    }

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Examples of stallone.doubles.EuclideanDistance

        return (kmeans(data, new EuclideanDistance(), k, 1000));
    }


    public IClustering kmeans(IDataSequence data, int k)
    {
        return (kmeans(data, new EuclideanDistance(), k, 1000));
    }

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Examples of stallone.doubles.EuclideanDistance

        return (kcenter(data, metric, k));
    }


    public IClustering kcenter(IDataInput data, int k)
    {
        return (kcenter(data, new EuclideanDistance(), k));
    }

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Examples of stallone.doubles.EuclideanDistance

        return (kcenter(data, new EuclideanDistance(), k));
    }


    public IClustering kcenter(IDataSequence data, int k)
    {
        return (kcenter(data, new EuclideanDistance(), k));
    }

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Examples of stallone.doubles.EuclideanDistance

        return regspace(data, metric, dmin);
    }


    public IClustering regspace(IDataInput data, double dmin)
    {
        return (regspace(data, new EuclideanDistance(), dmin));
    }

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Examples of stallone.doubles.EuclideanDistance

        return (regspace(data, new EuclideanDistance(), dmin));
    }


    public IClustering regspace(IDataSequence data, double dmin)
    {
        return (regspace(data, new EuclideanDistance(), dmin));
    }

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Examples of stallone.doubles.EuclideanDistance

        return (clustering);
    }


    public IClustering densitybased(IDataSequence data, double dmin, int minpts)
    {
        return densitybased(data, new EuclideanDistance(), dmin, minpts);
    }

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Examples of stallone.doubles.EuclideanDistance

        return (clustering);
    }


    public IClustering densitybased(IDataSequence data, int N)
    {
        return densitybased(data, new EuclideanDistance(), N);
    }

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