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classify a response variable that has more than two classes
the model
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Model the log odds ratio as a generalized additive models:
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for a seperating hyperplane
and
Equivalently, a separating hyperplane has the property that
for all
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You may try with other parameter values (e.g.
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Support Vector Machines can not handle nonlinearity.
What can we do?
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name | function |
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Linear kernel | |
Polynomial kernel | |
Radial kernel | |
Gaussian kernel | |
Laplacian kernel | |
Sigmoid kernel |
Suppose
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SVC
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SVM
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inner products / kernels
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functional form
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You may try with other parameter values (e.g.
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One-Versus-One (OVO) Classification
One-Versus-All (OVA) Classification
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The hinge loss + penalty form of support-vector classifier optimization:
SVM vs. Logistic Regression