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Extract the model coefficients from a standard Alteryx Count, Gamma, Linear, or Logistic Regression model. This is a simple macro, and one of its purposes is to be used as a template by users to create their own macros to extract information from an R model object.
Clustering with the pam (partitioning around medoids) function of R's cluster package. One benefit of this method of clustering over what can be done with the K-Centroids tool is that clusters can be based on a distance or dissimilarity matrix produced from the MB Affinity tool. The combination of the MB Affinity and K-Medoids is one way to see how items "group together" (such as products in a shopping basket) in a way that is often very useful.
Create partial dependency plots, which visually shows the relationship between a predictor variable and the predicted value of the target variable, as a well as an assessment of each predictor's relative "impact" (the range of values over which the predictor can "move" the predicted value of the target).