Quick SVM question for scikit-learn. When you train an SVM, it's something like
from sklearn import svm
s = svm.SVC()
s.fit(training_data, labels)
Is there any way for labels
to be a list of a non-numeric type? For instance, if I want to classify vectors as 'cat' or 'dog,' without having to have some kind of external lookup table that encodes 'cat' and 'dog' into 1's and 2's. When I try to just pass a list of strings, I get ...
ValueError: invalid literal for float(): cat
So, it doesn't look like just shoving strings in labels
will work. Any ideas?
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