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Simulation Scoring Tool

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Last modified: March 19, 2020

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. See Download and Use Predictive Tools.

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.

Warning

Do not 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.

Tool configuration

  • Name results of score simulation: The field name for the generated results. The field name must start with a letter and may 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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