Output Data Set
The OUTTREE= data set contains one observation for each
observation in the input data set, plus one observation
for each cluster of two or more observations (that is,
one observation for each node of the cluster tree).
The total number of output observations is usually
2n-1, where n is the number of input observations.
The density methods may produce fewer output observations
when the number of clusters cannot be reduced to one.
The label of the OUTTREE= data set identifies the type
of cluster analysis performed and is automatically
displayed when the TREE procedure is invoked.
The variables in the OUTTREE= data set are as follows:
- the BY variables, if you use a BY statement
- the ID variable, if you use an ID statement
- the COPY variables, if you use a COPY statement
- _NAME_, a character variable giving the name of the node. If the
node is a cluster, the name is CLn,
where n is the number of the cluster.
If the node is an observation, the name is OBn,
where n is the observation number.
If the node is an observation and the ID statement is
used, the name is the formatted value of the ID variable.
- _PARENT_, a character variable giving the
value of _NAME_ of the parent of the node
- _NCL_, the number of clusters
- _FREQ_, the number of observations in the current cluster
- _HEIGHT_, the distance or similarity between
the last clusters joined, as defined in
the section "Clustering Methods".
The variable _HEIGHT_ is used by the TREE
procedure as the default height axis.
The label of the _HEIGHT_ variable identifies
the between-cluster distance measure.
For METHOD=TWOSTAGE, the _HEIGHT_ variable contains the
densities at which clusters joined in the first
stage; for clusters formed in the second stage,
_HEIGHT_ is a very small negative number.
If the input data set contains coordinates,
the following variables appear in the output data set:
- the variables containing the coordinates
used in the cluster analysis.
For output observations that correspond to input
observations, the values of the coordinates are
the same in both data sets except for some slight
numeric error possibly introduced by standardizing
and unstandardizing if the STANDARD option is used.
For output observations that correspond to clusters
of more than one input observation, the values of
the coordinates are the cluster means.
- _ERSQ_, the approximate expected value
of R2 under the uniform null hypothesis
- _RATIO_, equal to [(1- _ERSQ_)/(1- _RSQ_)]
- _LOGR_, natural logarithm of _RATIO_
- _CCC_, the cubic clustering criterion
The variables _ERSQ_, _RATIO_, _LOGR_, and
_CCC_
have missing values when the number of clusters is
greater than one-fifth the number of observations.
If the input data set contains coordinates
and METHOD=AVERAGE, METHOD=CENTROID, or METHOD=WARD, then the
following variables appear in the output data set:
- _DIST_, the Euclidean distance between the
means of the last clusters joined
- _AVLINK_, the average distance between the
last clusters joined
If the input data set contains coordinates
or METHOD=AVERAGE, METHOD=CENTROID, or METHOD=WARD, then the
following variables appear in the output data set:
- _RMSSTD_, the root-mean-square standard
deviation of the current cluster
- _SPRSQ_, the semipartial squared multiple
correlation or the decrease in the proportion
of variance accounted for due to joining two
clusters to form the current cluster
- _RSQ_, the squared multiple correlation
- _PSF_, the pseudo F statistic
- _PST2_, the pseudo t2 statistic
If METHOD=EML, then the following
variable appears in the output data set:
- _LNLR_, the log-likelihood ratio
If METHOD=TWOSTAGE or METHOD=DENSITY, the
following variable appears in the output data set:
- _MODE_, pertaining to the modal clusters.
With METHOD=DENSITY, the _MODE_ variable indicates the number
of modal clusters contained by the current cluster.
With METHOD=TWOSTAGE, the _MODE_ variable gives the maximum
density in each modal cluster and the fusion density,
d*, for clusters containing two or more modal
clusters; for clusters containing no modal
clusters, _MODE_ is missing.
If nonparametric density estimates are requested (when
METHOD=DENSITY or METHOD=TWOSTAGE and the HYBRID option is not used;
or when the TRIM= option is used), the output data set contains
- _DENS_, the maximum density in the current cluster
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
