Please don't repost questions. Also, you didn't create a minimal reproducible example as suggested on stackoverflow: https://stackoverflow.com/help/minimal-reproducible-example That process would probably have shown you where the issue is. I highly recommend doing that next time. On 9/16/19 12:12 AM, Sayak Paul wrote:

I am working on a multi-label text classification problem. In order to encode the labels, I am using |MultiLabelBinarizer|. The labels of the dataset look like -

|[cs.AI,cs.CL,cs.CV,cs.NE,stat.ML][cs.CL,cs.AI,cs.LG,cs.NE,stat.ML][cs.CL,cs.AI,cs.LG,cs.NE,stat.ML][stat.ML,cs.AI,cs.CL,cs.LG,cs.NE][cs.CL,cs.AI,cs.LG,cs.NE,stat.ML]|

When I am using

|mlb =MultiLabelBinarizer()mlb.fit(labels)print(mlb.classes_)|

It gives me -

|array([' ',',','.','A','B','C','D','E','G','H','I','L','M','N','O','P','R','S','T','V','Y','[',']','a','c','h','m','s','t'],dtype=object)|

I (partially) fixed this problem by |mlb.fit([y_train])| and I got (I printed first 10 classes) -

|array(['[cs.AI, cs.CC]','[cs.AI, cs.CV]','[cs.AI, cs.CY]','[cs.AI, cs.DB]','[cs.AI, cs.DS]','[cs.AI, cs.GT]','[cs.AI, cs.HC]','[cs.AI, cs.IR]','[cs.AI, cs.LG, stat.ML]','[cs.AI, cs.LG]'],dtype=object)|

Ideally, it should output the individual classes (there may be something wrong in my code). When I am using |mlb.fit_transform([y_train])|, I am getting -

|array([[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]])|

Help would be very much appreciated.

Here's the corresponding StackOverflow issue: https://stackoverflow.com/questions/57917936/multilabelbinarizer-gives-indiv...

Sayak Paul |sayak.dev <http://sayak.dev>

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