Can someone share a code snippet that shows how to use SVM for text mining using scikit. I have seen an example of SVM on numerical data but not quite sure how to deal with text. I looked at http://scikit-learn.org/stable/auto_examples/document_classification_20newsgroups.html but couldn't find SVM.
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In text mining problems, text is represented by numeric values. Each feature represent a word and values are binary numbers. That gives a matrix with lots of zeros and a few 1s which means that the corresponding words exist in the text. Words can be given some weights according to their frequency or some other criteria. Then you get some real numbers instead of 0 and 1.
After converting the dataset to numerical values you can use this example: http://scikit-learn.org/dev/modules/generated/sklearn.svm.SVC.html#sklearn.svm.SVC
