Multivariate Methods • Normal Mixtures • Launch the Normal Mixtures Clustering Platform • Options
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Options
Normal Mixtures is the default clustering method, but you have the option to select Hierarchical or KMeans. If you select KMeans or Normal Mixtures, when you click OK, a Control Panel appears. See Iterative Clustering Control Panel.
Columns Scaled Individually
Use when variables do not share a common measurement scale, and you do not want one variable to dominate the clustering process. For example, one variable might have values that are between 0 and 1000, and another variable might have values between 0 and 10. In this situation, you can use the option so that the clustering process is not dominated by the first variable.
Johnson Transform
Fits a Johnson family distribution to each variable entered in Y, if Columns Scaled Individually is selected. Two of the Johnson families (Sb and Su) are considered and the fitting method uses maximum likelihood. See Distributions in the Basic Analysis book.
The Johnson transformations attempt to normalize the data, mitigating skewness and pulling outliers in toward the center of the distribution.
Note: If you select Johnson Transform but do not select Columns Scaled Individually, a single Johnson transformation is fit to values for all the variables entered in Y.

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Help created on 9/19/2017