Support Vectors
Linear Classifiers in Python
Michael (Mike) Gelbart
Instructor, The University of British Columbia
What is an SVM?
Linear classifiers (so far)
Trained using the hinge loss and L2 regularization
Support vector: a training example
not
in the flat part of the loss diagram
Support vector: an example that is incorrectly classified
or
close to the boundary
If an example is not a support vector, removing it has no effect on the model
Having a small number of support vectors makes kernel SVMs really fast
Max-margin viewpoint
The SVM maximizes the "margin" for linearly separable datasets
Margin: distance from the boundary to the closest points
Max-margin viewpoint
The SVM maximizes the "margin" for linearly separable datasets
Margin: distance from the boundary to the closest points
Let's practice!
Linear Classifiers in Python
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