Description Usage Arguments Details Value See Also Examples

View source: R/assigncluster.R

Maps a vector of cluster numbers to another categorical vector,
yielding a new vector of matching cluster numbers. Useful for distributing
cluster numbers back out to the original observations in cases where the
clustering was performed on a table of unique levels rather than directly
on the observations (such as with `greenclust`

).

1 | ```
assign.cluster(x, clusters, impute = FALSE)
``` |

`x` |
a factor or character vector representing a categorical variable |

`clusters` |
a named numeric vector of cluster numbers, such as an
object returned by |

`impute` |
a boolean controlling the behavior when a value in |

Any categories in `x`

that do not exist in `names(clusters)`

are given a cluster of `NA`

, or (if `impute`

is `TRUE`

)
assigned the cluster number that is most-frequently used for the other
existing categories, with ties going to the lowest cluster number. If
there are no matching clusters for any of the categories in `x`

,
imputation will simply use the first cluster number in `clusters`

.

If there are duplicate names in `clusters`

, the first occurrence
takes precedence.

A factor vector of the same length as `x`

, representing
assigned cluster numbers.

`greenclust`

, `greencut`

,
`greenplot`

1 2 3 4 5 6 | ```
# Cluster feed types based on number of "underweight" chicks
grc <- greenclust(table(chickwts$feed,
ifelse(chickwts$weight < 200, "Y", "N")))
# Assign clusters to each original observation
feed.clustered <- assign.cluster(chickwts$feed, greencut(grc))
table(chickwts$feed, feed.clustered)
``` |

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