K-Means Visualizations

The following tables and options are available for k-Means visualizations.

Model Information table

This table provides information about the type of model, inputs and various results from the model. Included is the number of features, distance measure used in fitting the model, the numbers and sizes of the clusters, including percentages of the sample, the ratio of the largest to the smallest cluster size and the Average Silhouette measures of overall clustering quality, which is expressed on a 0-1 scale, with larger values indicating better clustering solutions. Also shown are the total and average within clusters sums of squares and the average between clusters sum of squares.

Predictor Importance chart

This chart displays bars representing the predictors in descending order of relative importance for predicting the target, as determined by a variance-based sensitivity analysis algorithm. The values for each predictor are scaled so that they add to 1.

Hovering over a particular bar results in a table on the right showing the predictor importance values for that predictor, along with descriptive statistics. For scale features, these are mean, standard deviation and sample size. For categorical features, these are the counts and percentages in each category.

Cluster Sizes chart

A horizontal bar chart displaying the relative sizes of the clustering in descending order. Hovering over a bar shows the precise percentage of the total number of instances in that cluster based on the K-Means model.

Next steps

Like your visualization? Why not deploy it? For more information, see Deploy a model.