lsvmnode properties

The Linear Support Vector Machine (LSVM) node enables you to classify data into one of two groups without overfitting. LSVM is linear and works well with wide data sets, such as those with a very large number of records.

Table 1. lsvmnode properties

lsvmnode Properties	Values	Property description
intercept	flag	Includes the intercept in the model. Default value is True.
target_order	Ascending Descending	Specifies the sorting order for the categorical target. Ignored for continuous targets. Default is Ascending.
precision	number	Used only if measurement level of target field is Continuous. Specifies the parameter related to the sensitiveness of the loss for regression. Minimum is 0 and there is no maximum. Default value is 0.1.
exclude_missing_values	flag	When True, a record is excluded if any single value is missing. The default value is False.
penalty_function	L1 L2	Specifies the type of penalty function used. The default value is L2.
lambda	number	Penalty (regularization) parameter.
calculate_variable_importance	flag	For models that produce an appropriate measure of importance,this option displays a chart that indicates the relative importance of each predictor in estimating the model. Note that variable importance may take longer to calculate for some models, particularly when working with large datasets, and is off by default for some models as a result. Variable importance is not available for decision list models.