# dissimilarity.object

From cluster v1.4-1
by Martin Maechler

##### Dissimilarity Matrix Object

Objects of class `"dissimilarity"`

representing the dissimilarity
matrix of a dataset.

- Keywords
- cluster

##### Value

- The dissimilarity matrix is symmetric, and hence its lower triangle
(column wise) is represented as a vector to save storage space.
If the object, is called
`do`

, and`n`

the number of observations, i.e.,`n <- attr(do, "Size")`

, then for $i < j <= n$,="" the="" dissimilarity="" between="" (row)="" i="" and="" j="" is=""`do[n*(i-1) - i*(i-1)/2 + j-i]. The length of the vector is $n*(n-1)/2$, i.e., of order $n^2$.`

`"dissimilarity"`

objects also inherit from class`dist`

and can use`dist`

methods, in particular,`as.matrix`

, such that $d_{ij}$ from above is just`as.matrix(do)[i,j]`

.The object has the following attributes:

Size the number of observations in the dataset. Metric the metric used for calculating the dissimilarities. Possible values are "euclidean", "manhattan", "mixed" (if variables of different types were present in the dataset), and "unspecified". Labels optionally, contains the labels, if any, of the observations of the dataset. NA.message optionally, if a dissimilarity could not be computed, because of too many missing values for some observations of the dataset.

##### GENERATION

`daisy`

returns this class of objects.
Also the functions `pam`

, `clara`

, `fanny`

,
`agnes`

, and `diana`

return a `dissimilarity`

object,
as one component of their return objects.

##### METHODS

The `"dissimilarity"`

class has methods for the following generic
functions: `print`

.

##### See Also

*Documentation reproduced from package cluster, version 1.4-1, License: GPL version 2 or later*

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