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I have a set of training data and I need to build a classifier with it. There are just two classes of elements, and the values of the attributes are all integer, like:

$ \ [V_{11}, V_{12}, \ldots, V_{1N}] \in C_1 \\ \ [V_{21}, V_{22}, \ldots, V_{2N}] \in C_2 \\ \vdots \\ \ [V_{M1}, V_{M2}, \ldots, V_{MN}] \in C_M \\ \\ \ C_i \in [Class\_1, Class\_2] $

What kind of classifier should I use? I've been reading about Bayes classifiers but I'm not really sure if it would fit in here.

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    Try replacing "\\" with "\\\". Char escaping problems maybe.2012-05-04

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At the end I used a Perceptron. The problem was actually pretty basic and the perceptron led to a stable state in just two training iterations.