Looks like the value error is haunting me still. I am trying to load a
multi-label libSVM format data file (sample pasted below) as:
X_train, y_train = load_svmlight_file("testtrain.txt", dtype=np.int32,
multilabel=True)
which gives me at-least 2 issues which confuse me. Help me here.
[1]. ValueError: empty string for float()
I did specify "np.int32". [Note that numpy is imported as 'np']. Yet,
it seemed to expect float for feature values. The error comes even if
I remove the dtype altogether.
[2]. ValueError: Feature indices in SVMlight/LibSVM data file should
be sorted and unique.
Is there a limitation as such? Because my dataset is from LSHTC
(http://lshtc.iit.demokritos.gr/LSHTC4_GUIDELINES) and the website
specifically mentions it to be in libSVM format.
Sample data below. I can see that the features are not sorted.
314523, 165538, 76255, 335416, 416827 1250536:1 1744638:1 298526:1
1568238:1 77076:1 1327541:1 1416569:1 1586020:1 1700948:1 652007:1
1815811:1 488832:2 572742:1 1137332:2 1473311:1 513820:1 1210088:1
423304:1 1357328:1 1673413:1 214525:1 1733491:1 1313723:1 1540893:5
1465710:1 2021871:1 1936077:1 513790:1 660115:1 1287792:3 481092:1
843169:2 572336:1 460447:1 97802:1 1397861:3 1284496:1 1875794:1
1972806:1 1457483:1 227881:3 410359:1 265208:7 985823:1 331158:1
85847:1 1402995:1 1710579:1 102853:1 1274838:1 1105861:2 892257:1
951474:1 1004657:1 234275:1 830416:1 563647:3 1564710:4 1156150:1
970168:2 592526:3 550210:1 453755:1 705700:1 1470603:1 903090:1
614785:2 1151929:1 1303404:1 2070888:1 1837036:1 1360760:1 1611236:1
955673:1 49164:2 704224:2 1137133:1 1298082:1 977746:1 9364:1
1267431:1
Specs
=====
python 2.6.6
scipy - 0.13.3
numpy - 1.8.0
scikit-learn - 0.14.1
- Anitha
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