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Variable Importance Data Function for Spotfire® using Spotfire® Data Science - Workbench 1.0.0

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This is example of the data function for Spotfire® built in Spotfire® Data Science - Workbench (also known as Statistica). The purpose of this example is to help users in building Statistica data functions.


This is example dxp where Statistica data function is used to identify the best predictors for the classification task. Together with that, some basic data cleaning is applied inside the data function before the actual best predictors evaluation. Variable importance is computed on an interactively selected subset of the data with the possibility to define variables coming to analysis from dropdowns. More info about Statistica data functions here.

For the construction of the data function the no-code environment of Spotfire Data Science - Workbench visual workflows is used (if you are not familiar with Statistica workspaces, please visit this community article).

What this example shows:

  • Example of more steps of computation inside the data function (data cleaning and variable importance)
  • Example of one Input and one Output data function  with parametrization involved
  • Example of variable names  parametrization
  • Example of on-demand triggering data function computed on a subset of data defined by marking

Feature highlights: Parameterization of variable selection.

If you are interested in building the Statistica data functions, please find additional examples here

Initial Release (version 1.0.0)

Published: December 2019

This release includes Spotfire Data Science - Workbench (Statistica) workspace used for building the data function as well as dxp where this data function is applied.

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