Describe Spatial Statistics Model File (Spatial Statistics)

Summary

Describes the contents and diagnostics of a spatial statistics model file.

Learn more about spatial statistics model files

Usage

  • The primary outputs of this tool are geoprocessing output messages that describe the characteristics and contents of the input model file. To access the messages, hover over the progress bar and click the pop-out button, or expand the messages section in the Geoprocessing pane. You can also access the messages for a previous run of the tool through the geoprocessing history.

    The messages include the following information and tables:

    • The tool and method used to create the spatial statistics model file.
    • The Model Parameters table describes the variable to predict and the explanatory variables used to create the model. The table also contains units for each variable so you can confirm that they align with the prediction variables when using the model to make predictions. You can set the variable description and units using the Set Spatial Statistics Model File Properties tool.
    • The messages and model diagnostics from the tool used to create the model file. See the documentation for the associated tool for explanations of the messages and diagnostics.

    Note:

    If no validation data was withheld during the model training process, some of the diagnostics will not display in the messages. Use caution before making predictions with such models.

    For forest-based classification and regression, Out Of Bag (OOB) errors do not appear in the messages because they are not saved in the model file. For presence-only prediction, the counts of presence and background points used to train the model and the cross-validation results do not appear because this information may be sensitive or confidential.

    Caution:

    Some model diagnostics (such as the confusion matrix) and the contents of the model file can potentially be used to reverse-engineer the input data that was used to create the file. Share model files with caution if the data used to train the model is confidential or sensitive.

  • You can create the model file using the Output Trained Model File parameter in the Generalized Linear Regression, Forest-based and Boosted Classification and Regression, or Presence-only Prediction tools.

    For models created by the Generalized Linear Regression, the messages will display the model type that was used (continuous, binary, or count). For the Forest-based and Boosted Classification and Regression tool, the messages will display whether a forest-based or gradient boosted model for regression or classification was used. For the Presence-only Prediction tool, the messages will display whether background points were used.

  • The following are potential applications of this tool:

    • Understand the variables stored in the model file by reviewing their description and units. Then use the Predict Using Spatial Statistics Model File tool for predictions.
    • View the model diagnostics to assess model quality.

Parameters

LabelExplanationData Type
Input Model File

The spatial statistics model file that will be described.

File

Derived Output

LabelExplanationData Type
Explanatory Training Variables

A list of the explanatory training variables used to train the model file.

String
Explanatory Training Distance Features

A list of the explanatory training distance features used to train the model file.

String
Explanatory Training Rasters

A list of the explanatory training rasters used to train the model file.

String

arcpy.stats.DescribeSSMFile(input_model)
NameExplanationData Type
input_model

The spatial statistics model file that will be described.

File

Derived Output

NameExplanationData Type
explanatory_variables

A list of the explanatory training variables used to train the model file.

String
explanatory_distance_features

A list of the explanatory training distance features used to train the model file.

String
explanatory_rasters

A list of the explanatory training rasters used to train the model file.

String

Code sample

DescribeSSMFile example 1 (Python window)

The following Python window script demonstrates how to use the DescribeSSMFile function.

import arcpy
arcpy.stats.DescribeSSMFile("C:/MyData/input_modelfile.ssm")
DescribeSSMFile example 2 (stand-alone script)

The following stand-alone Python script demonstrates how to use the DescribeSSMFile function.

# Print the properties of a spatial statistics model file
# Import modules
import arcpy

# Set the current workspace
arcpy.env.workspace = "C:/MyData"

# Run tool 
arcpy.stats.DescribeSSMFile("input_modelfile.ssm")

# Print geoprocessing messages
print(arcpy.GetMessages())

Environments

This tool does not use any geoprocessing environments.

Related topics