Generalized Linear Model Properties

The following properties are available for the Generalized Linear Model:
Name
enables you to specify the name for this model.
specifies whether the informative missingness algorithm is used. For more information, see Missing Values.
Distribution
specifies the distribution used to model the response variable.
specifies the link function used to relate the linear model to the distribution of the response variable. Available link functions are different for each distribution and are shown in the following table:
Distribution
Available Link Functions
Beta
Logit, Probit, Log-log, C-log-log
Binary
Logit, Probit, Log-log, C-log-log
Exponential
Log, Identity
Gamma
Log, Identity, Recip
Geometric
Log, Identity
Inverse Gaussian
Power(-2), Log, Identity
Negative Binomial
Log, Identity
Normal
Log, Identity
Poisson
Log, Identity
Convergence
  • Override function convergence enables you to manually specify the function convergence value.
  • Value specifies the function convergence value when Override function convergence is selected. When you specify a larger value, the model will converge sooner. This reduces the amount of time spent training the model, but it can create a suboptimal model.
  • Override gradient convergence enables you to manually specify the gradient convergence value.
  • Value specifies the gradient convergence value when Override gradient convergence is selected. When you specify a larger value, the model will converge sooner. This reduces the amount of time spent training the model, but it can create a suboptimal model.
  • Maximum iterations specifies the maximum number of iterations performed during model training. If you specify a relatively small value, you reduce the amount of time spent training the model, but it can create a suboptimal model.
Note: When you specify a gradient convergence or function convergence criterion, it is possible for the model to converge based on an internal convergence criterion before your specified criterion is reached. The reason for convergence is on the Convergence tab of the details table.
Assessment
  • Use default number of bins specifies whether you want to use the default number of bins or to set your own value. By default, measure variables are grouped into 20 bins.
  • Number specifies the number of bins to use when the Use default number of bins property is not selected. You must specify an integer value between 5 and 100.
  • Tolerance specifies the tolerance value that is used to determine the convergence of the iterative algorithm that estimates the percentiles. Specify a smaller value to increase the algorithmic precision.
specifies whether the Residual Plot and Assessment windows appear in the model pane.
Last updated: January 8, 2019