Description Usage Arguments Value Examples

This function computes various weighted sum-of-squares criteria for a given partition of a dataset described by numerical features.

1 | ```
weightedss(X, cl, w = NULL)
``` |

`X` |
a matrice or a dataframe of size |

`cl` |
a vector of integers of length |

`w` |
a numerical vector of length |

`bss.per.feature` |
a numerical vector of length |

`wss.per.feature` |
a numerical vector of length |

`bss.per.cluster` |
a numerical vector of length |

`wss.per.cluster` |
a numerical vector of length |

`bss` |
a scalar representing the weighted between sum-of-squares of the partition.
It may be computed as the sum over |

`wss` |
a scalar representing the weighted within sum-of-squares of the partition.
It may be computed as the sum over |

1 2 3 4 5 6 7 8 9 10 11 | ```
data(iris)
out <- weightedss(X = iris[,1:4], cl = as.numeric(iris$Species))
out$bss.per.feature
out$bss.per.cluster
out$bss
w <- c(0.3,0.3,0.2,0.2)
out <- weightedss(X = iris[,1:4], cl = as.numeric(iris$Species), w=w)
out$bss.per.feature
out$bss.per.cluster
out$bss
``` |

vimpclust documentation built on Jan. 8, 2021, 5:34 p.m.

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