get.dmetrics

Displays the distance metric options for calculation of the distances between the data objects and the cluster centers.

cluster

Partitioning clustering divides the objects in a data set into non-overlapping subsets or clusters by using the prototype-based probabilistic and possibilistic clustering algorithms. This package covers a set of the functions for Fuzzy C-Means (Bezdek, 1974) <doi:10.1080/01969727308546047>, Possibilistic C-Means (Krishnapuram & Keller, 1993) <doi:10.1109/91.227387>, Possibilistic Fuzzy C-Means (Pal et al, 2005) <doi:10.1109/TFUZZ.2004.840099>, Possibilistic Clustering Algorithm (Yang et al, 2006) <doi:10.1016/j.patcog.2005.07.005>, Possibilistic C-Means with Repulsion (Wachs et al, 2006) <doi:10.1007/3-540-31662-0_6> and the other variants of hard and soft clustering algorithms. The cluster prototypes and membership matrices required by these partitioning algorithms are initialized with different initialization techniques that are available in the package 'inaparc'. As the distance metrics, not only the Euclidean distance but also a set of the commonly used distance metrics are available to use with some of the algorithms in the package.

Zeynel Cebeci

ppclust

Probabilistic and Possibilistic Cluster Analysis

Figen Yildiz

Alper Tuna Kavlak

Cagatay Cebeci

Hasan Onder

get.dmetrics function

<dl> <dt>dmt</dt>
<dd>a string for the type of distance metrics. The default is all for the list of all of the distance metrics which are available in the package. The other options are l1, l2, lp, sl2 and sc for L1, L2, Lp, squared L2 and squared Chord, respectively.</dd></dl>

Arguments

Author

List the names of distance metrics — get.dmetrics

<dl>

 <dt>dmt</dt>
<dd>a string for the type of distance metrics. The default is all for the list of all of the distance metrics which are available in the package. The other options are l1, l2, lp, sl2 and sc for L1, L2, Lp, squared L2 and squared Chord, respectively.</dd>

</dl>

get.dmetrics: List the names of distance metrics

Description

Usage

Value

Arguments

Author

References

See Also

Examples