K Means NCluster=<k> Report Options | JMP 13.2

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Multivariate Methods • K Means Cluster • K Means NCluster=<k> Report • K Means NCluster=<k> Report Options

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K Means NCluster=<k> Report Options

Each K Means NCluster=<k> report contains the following options:

Shows a plot of the points and clusters in the first two principal components of the data. Circles are drawn around the cluster centers. The size of the circles is proportional to the count inside the cluster. The shaded area is the 50% density contour around the mean, and indicates where 50% of the observations in that cluster would fall (Mardia et al., 1980). Below the plot is an option to save the cluster colors to the data table. The eigenvalues are shown in decreasing order.

Contains the following options for controlling the appearance of the Biplot:

Show Biplot Rays

Shows the biplot rays. The labeled rays show the directions of the covariates in the subspace defined by the principal components. They represent the degree of association of each variable with each principal component.

Biplot Ray Position

Enables you to specify the position and radius scaling of the biplot rays. By default, the rays emanate from the point (0,0). In the plot, you can drag the rays or use this option to specify coordinates. You can also adjust the scaling of the rays to make them more visible with the radius scaling option.

Assigns markers that identify the clusters to the rows of the data table.

Shows a three-dimensional biplot of the data. Available only when there are three or more variables.

Parallel Coord Plots

Creates a parallel coordinate plot for each cluster. The plot report has options for showing and hiding the data and means. For details, see “Parallel Plots” in the Essential Graphing book.

Scatterplot Matrix

Creates a scatterplot matrix using all of the Y variables in a separate window.

Save Colors to Table

Assigns colors that identify the clusters to the rows of the data table.

Saves the following two columns to the data table:

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The Cluster column contains the number of the cluster to which the given row is assigned.

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(Not available for Self Organizing Maps.) The Distance column contains the squared Euclidean distance between the given observation and its cluster mean. For each variable, the difference between the observation’s value and the cluster mean on that variable is divided by the overall standard deviation for the variable. These scaled differences are squared and summed across the variables.

Save Cluster Formula

Saves a formula column called Cluster Formula to the data table. This is the formula that identifies cluster membership for each.

Simulate Clusters

Creates a new data table containing simulated cluster observations on the Y variables, using the cluster means and standard deviations.

Removes the clustering report.

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Help created on 9/19/2017