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in AI and Deep Learning by (50.2k points)

When creating a libsvm training file, how do you differentiate between a nominal attribute versus a numeric attribute? I'm trying to encode certain nominal attributes as integers, but I want to ensure libsvm doesn't misinterpret them as numeric values. Unfortunately, libsvm's site seems to have very little documentation. Pentaho's docs seem to imply libsvm makes this distinction, but I'm still not clear how it's made.

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Just use a separate binary feature for each value of each nominal attribute.

The way SVMs are expressed, all attributes/features are numeric and class labels are nominal. Nominal attributes are essentially faked by using commonly exclusive binary features.

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