Generalized Linear Models (GLM) solves classification problems using logistic regression.
The default settings are designed so that they should work for most cases.
Click Restore to restore the default values.
When you are done specifying algorithm settings, click OK to continue.
For more information about these settings, see Oracle Data Mining Concepts.
GLM supports the following build settings for regression:
Confidence is a positive number that is less than 1.0. It indicates the degree of certainty that the true coefficient lies within the confidence bounds computed by the model. The default confidence is 0.95.
Generate Diagnostics Table allows the generation of a table to contain row-level diagnostics. The default is to not generate such a table.
The Reference Target Class is the target value used as a reference in a binary logistic regression model. Probabilities are produced for the other (non-reference) class. By default, the algorithm chooses the value with the highest prevalence. If there are ties, the attributes are sorted alpha-numerically in ascending order.
The default for Reference Target Class is System Determined, that is, the algorithm determines the value. You can select one of the values of the class from the list. If the values of the target are 0 and 1, the choices in the list are System Determined, 0, and 1.
Ridge regression is a technique that compensates for multicollinearity (multivariate regression with correlated predictors). Oracle Data Mining supports ridge regression for both regression and classification mining functions.
The following settings control ridge regression:
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