Kernel SVMs

Linear Classifiers in Python

Michael (Mike) Gelbart

Instructor, The University of British Columbia

Transforming your features

Linear Classifiers in Python

Transforming your features

Linear Classifiers in Python

Transforming your features

$\textrm{transformed feature} =$

$ (\textrm{original feature})^2$

Linear Classifiers in Python

Transforming your features

$\textrm{transformed feature} =$

$ (\textrm{original feature})^2$

Linear Classifiers in Python

Transforming your features

$\textrm{transformed feature} =$

$ (\textrm{original feature})^2$

Linear Classifiers in Python

Kernel SVMs

from sklearn.svm import SVC

svm = SVC(gamma=1)    # default is kernel="rbf"

Linear Classifiers in Python

Kernel SVMs

from sklearn.svm import SVC

svm = SVC(gamma=0.01) # default is kernel="rbf"

  • smaller gamma leads to smoother boundaries
Linear Classifiers in Python

Kernel SVMs

from sklearn.svm import SVC

svm = SVC(gamma=2)    # default is kernel="rbf"

  • larger gamma leads to more complex boundaries
Linear Classifiers in Python

Let's practice!

Linear Classifiers in Python

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