Simulation Scoring Tool Icon

Simulation Scoring Tool

Last modified: May 17, 2023

The Simulation Scoring tool takes a sample from an approximation of a model object error distribution. Whereas standard scoring attempts to predict the mean predicted value, Simulation Scoring also considers the error distribution to provide a range of possible values.

This tool uses the R tool. Go to Options > Download Predictive Tools and sign in to the Alteryx Downloads and Licenses portal to install R and the packages used by the R tool. Go to Download and Use Predictive Tools for more information.

Connect Inputs

Error Distribution Sampling Methodology

  • If you are scoring an LM model, the error distribution can be directly sampled due to the properties of LMs.
  • If you are scoring other models (non-LM), homoscedasticity of the error distributions with respect to the predictors is assumed. This allows a single error distribution to be calculated by scoring the model against a validation set. That error distribution is then sampled and added to the score results for the incoming data.

Don't connect this input when the incoming model object uses a Linear Regression tool.

  • S anchor: The simulation data to score. This must contain all of the fields (with identical types and names) used to create the associated predictive model.

Configure the Tool

  • Name results of score simulation: The field name for the generated results. The field name must start with a letter and can contain letters, numbers, and the special characters period (".") and underscore ("_"). Note that R is case-sensitive.
  • The number of records to score at a time: The tool can break the input data into chunks, score a chunk at a time, and thereby avoid R's in-memory processing limitation. This option controls the maximal number of incoming records contained in each chunk of data.
  • How many samples from error distribution per iteration: The number of draws from the model's error distribution for each incoming record.
  • Set Random Seed (Optional): Specify a random seed. This option is hidden if there is a seed field in the data to be scored.

View the Output

  • D anchor: The data to be scored, along with the simulated score.
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