SvmModel new

---

__init__(self, name=None)

[ALPHA] Create a ‘new’ instance of a Support Vector Machine model.

Parameters:

name : unicode (default=None)

User supplied name.

Returns:

: <bound method AtkEntityType.__name__ of <trustedanalytics.rest.jsonschema.AtkEntityType object at 0x7f9e68702090>>

Support Vector Machine [R72] is a supervised algorithm used to perform binary classification. A Support Vector Machine constructs a high dimensional hyperplane which is said to achieve a good separation when a hyperplane has the largest distance to the nearest training-data point of any class. This model runs the MLLib implementation of SVM [R73] with SGD [R74] optimizer. The SVMWithSGD model is initialized, trained on columns of a frame, used to predict the labels of observations in a frame, and tests the predicted labels against the true labels. During testing, labels of the observations are predicted and tested against the true labels using built-in binary Classification Metrics.

footnotes

[R72]

https://en.wikipedia.org/wiki/Support_vector_machine

[R73]

https://spark.apache.org/docs/1.3.0/mllib-linear-methods.html

[R74]

https://en.wikipedia.org/wiki/Stochastic_gradient_descent