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svmnode properties
Last updated: Feb 11, 2025
svmnode properties

SVM node iconThe Support Vector Machine (SVM) node enables you to classify data into one of two groups without overfitting. SVM works well with wide data sets, such as those with a very large number of input fields.

Example

node = stream.create("svm", "My node")
# Expert tab
node.setPropertyValue("mode", "Expert")
node.setPropertyValue("all_probabilities", True)
node.setPropertyValue("kernel", "Polynomial")
node.setPropertyValue("gamma", 1.5)
Table 1. svmnode properties
svmnode Properties Values Property description
all_probabilities flag  
stopping_criteria
1.0E-1
1.0E-2
1.0E-3
1.0E-4
1.0E-5
1.0E-6
 Determines when to stop the optimization algorithm.
regularization number Also known as the C parameter.
precision number Used only if measurement level of target field is Continuous.
kernel
RBF
Polynomial
Sigmoid
Linear
 Type of kernel function used for the transformation. RBF is the default.
rbf_gamma number Used only if kernel is RBF.
gamma number Used only if kernel is Polynomial or Sigmoid.
bias number  
degree number Used only if kernel is Polynomial.
calculate_variable_importance flag  
calculate_raw_propensities flag  
calculate_adjusted_propensities flag  
adjusted_propensity_partition
Test
Validation