Converting categorical variables to int / float?

[sherrylau]

Hi, I am trying to apply your k-prototypes algorithm on my dataset. I have a list of categorical and numerical attributes. Following the soybean examples, i got the following error:
Traceback (most recent call last):

File "", line 2, in
kmodes_huang.cluster(cas_orc_join_nonus_cat, init_method='Huang')

File "/Users/212448740/Desktop/python_ml/kmodes.py", line 75, in cluster
self._perform_clustering(x, _args, verbose=0, *_kwargs)

File "/Users/212448740/Desktop/python_ml/kmodes.py", line 108, in _perform_clustering
self.init_centroids(x)

File "/Users/212448740/Desktop/python_ml/kmodes.py", line 190, in init_centroids
self.centroids[ik, iattr] = random.choice(choices)

ValueError: could not convert string to float

Is that mean i have to convert all the categorical attributes into 0, 1, 2, etc for the function to works?

Sherry

[sherrylau]

Actually that error is from k-modes.cluster instead of k-prototypes.cluster

[nicodv]

Yes, that seems to be a limitation. Let me see what I can do. Was planning a significant rewrite anyway.

For now, you could use sklearn's LabelEncoder to convert to integers: http://scikit-learn.org/dev/modules/generated/sklearn.preprocessing.LabelEncoder.html

[sherrylau]

I will try that! Thanks for your quick response!

[nicodv]

Thanks for the motivation fo rewriting the package. :)

Try again, using strings directly should now work.

[sherrylau]

Thanks! Glad that you wrote this package!