Description Usage Arguments Details Value Author(s) References See Also Examples

Initializes the cluster prototypes matrix by using K-means++ algorithm which has been proposed by Arthur and Vassilvitskii (2007).

1 | ```
kmpp(x, k)
``` |

`x` |
a numeric vector, data frame or matrix. |

`k` |
an integer specifying the number of clusters. |

K-means++ (Arthur & Vassilvitskii, 2007) is usually reported as an efficient approximation algorithm in overcoming the poor clustering problem with the standard K-means algorithm. K-means++ is an algorithm that merges MacQueen's second method with the ‘Maximin’ method to initialize the cluster prototypes (Ji et al, 2015). K-means++ initializes the cluster centroids by finding the data objects that are farther away from each other in a probabilistic manner. In K-means++, the first cluster protoype (center) is randomly assigned. The prototypes of remaining clusters are determined with a probability of *{md(x')}^2/∑_{i=1}^{n} md({x_i})^2*, where *md(x)* is the minimum distance between a data object and the previously computed prototypes.

The function `kmpp`

is an implementation of the initialization algorithm of K-means++ that is based on the code‘k-meansp2.R’, authored by M. Sugiyama. It needs less execution time due to its vectorized distance computations.

an object of class ‘inaparc’, which is a list consists of the following items:

`v` |
a numeric matrix containing the initial cluster prototypes. |

`ctype` |
a string representing the type of centroid, which used to build prototype matrix. Its value is ‘obj’ with this function because the cluster prototypes are the objects selected by the algorithm. |

`call` |
a string containing the matched function call that generates this sQuoteinaparc object. |

Zeynel Cebeci, Cagatay Cebeci

Arthur, D. & Vassilvitskii. S. (2007). K-means++: The advantages of careful seeding, in *Proc. of the 18th Annual ACM-SIAM Symposium on Discrete Algorithms*, p. 1027-1035. url:http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf

M. Sugiyama, ‘mahito-sugiyama/k-meansp2.R’. url:https://gist.github.com/mahito-sugiyama/ef54a3b17fff4629f106

`aldaoud`

,
`ballhall`

,
`crsamp`

,
`firstk`

,
`forgy`

,
`hartiganwong`

,
`inofrep`

,
`inscsf`

,
`insdev`

,
`kkz`

,
`ksegments`

,
`ksteps`

,
`lastk`

,
`lhsmaximin`

,
`lhsrandom`

,
`maximin`

,
`mscseek`

,
`rsamp`

,
`rsegment`

,
`scseek`

,
`scseek2`

,
`spaeth`

,
`ssamp`

,
`topbottom`

,
`uniquek`

,
`ursamp`

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