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Last updated: Feb 11, 2025
The 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)
Properties |
Values | Property description |
---|---|---|
|
flag | |
|
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Determines when to stop the optimization algorithm. |
|
number | Also known as the C parameter. |
|
number | Used only if measurement level of target field is . |
|
|
Type of kernel function used for the transformation. is the
default. |
|
number | Used only if is . |
|
number | Used only if is or . |
|
number | |
|
number | Used only if is . |
|
flag | |
|
flag | |
|
flag | |
|
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