What is the VC dimension for logistic regresion? I know that the VC dimension for a perceptron is 3, but what is it for a logistic regression model?

A logistic regression model can shatter any problem that can be shattered by a perceptron (i.e. if the perceptron can classify it without error, regardless of how the data are labelled, so can the logistic regression model), and vice versa, so their VC dimensions are the same. BTW I think the VC dimension of a perceptron is only 3 for a two-dimensional problem, in general it is one more than the number of dimensions/attributes/features.
