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DATA MINING from data to information Ronald
Westra Dep. Mathematics Maastricht University 7
December, 2006
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SUPPORT VECTOR MACHINES

• Theory

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The VC dimension (Vapnik Chervonenkis dimension)
is a measure of the capacity of a statistical
classification algorithm. Consider a
classification model f with some parameter vector
?. The model f can shatter a set of data points
if, for all assignments of labels to those data
points, there exists a ? such that the model f
makes no errors when evaluating that set of data
points. The VC dimension of a model f is the
maximum h such that some data point set of
cardinality h can be shattered by f.
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