[FIXED] Non-Integer Class Labels Scikit-Learn

Issue

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?

Solution

The recent version of sklearn is able to use string as the labels. For example:

from sklearn.svm import SVC
clf = SVC()
x = [[1,2,3], [4,5,6]]
y = ['dog', 'cat']
clf.fit(x,y)

yhat = clf.predict([[1,2,5]])
print yhat[0]

Answered By - tqjustc