loading libsvm text file in scikit

Question

I have a text file called "test.txt" which contains data in libsvm format. Data in this file is represented as follows:

165475 0:246870 1124384:2 342593:7 1141651:1 297582:1 1186846:1 17725:1 656602:1 
463304:1 766612:1 573309:1 290046:1 748198:1 216665:1 950594:2 909004:1 29008:1      
105623:1 5018:5 806027:1 1125729:1 757846:1 1023921:2 612980:1 120767:1 51340:1 
108172:5 674420:2

where 1st term represents the label and remaining represents the feature and its weight(separated by : ).This is a very huge file(with every label having lots of features and weights).

I am using scikit with ipython notebook and want to load this data in notebook to start processing it.

Can someone tell how to do that.Thanks in advance.

Answer 1

Use load_svmlight_file from sklearn.datasets.