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Asked: 2026-06-05T22:07:30+00:00

I’ve just recently started using libsvm. I’ve been trying for awhile to train my

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I’ve just recently started using libsvm. I’ve been trying for awhile to train my features get the model and then do a prediction with corresponding features. Unforunately I contiously get wrong file format. I’ve routinely done this measure cut my features and then train on them, which I get a model.

This is how I train to get the model.
I’m doing this via unix command line btw.

./svm-train -t 0 -b 1 svmtrainModel1Revised.txt TrainedModel1.svm

0 1:8.109121    2:11.063075 3:9.265099 4:7.392232  5:9.577386
0 1:7.497237    2:10.314889 3:9.330452 4:8.658748 5:9.493017
0 1:7.579283    2:9.853208 3:9.863712 4:8.48306 5:9.84812
1 1:7.683603    2:10.323639 3:10.616027 4:7.039438 5:10.321418
1 1:7.645213    2:9.742212 3:9.957533 4:8.810831 5:8.86067
0 1:7.738999    2:9.956453 3:9.643299 4:8.553764 5:9.824224
1 1:7.968907    2:10.610946 3:9.061123 4:7.84069 5:9.793263

The model I get from above I predict based on that.

./svm-predict -b 1 svmtest1RevisedA.txt TrainedModel1.svm labelmodel1.txt

These features are in the same format as above, except they are lacking the ground truth.

8.139867    10.146595   9.554127    8.409128    9.380923
7.691873    9.820682    9.777709    9.136581    9.038513
8.629565    10.684548   9.192018    9.031779    9.733009
7.796154    10.871736   9.113837    7.329961    10.071653
7.235544    9.994834    10.601161   8.720384    10.112152
8.008006    10.75276    10.755063   7.517268    9.415618
7.857692    9.936756    9.556366    8.941176    8.933603
7.806821    9.934397    9.324827    8.422852    8.797105

There are no commas and there is only a space between each element,but when i got to predict it tells me Wrong input format at line 1. please help.

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1 Answer

  1. Editorial Team

    You need to make the training labels either 1 or -1. This is standard within the SVM sub-world of the machine learning world. Also you might want to take out any tabs and make sure your whitespace only consists of spaces.

    Here are a few lines from a file I trained with using libsvm: 

    -1 1:0.000000 2:0.274121 3:0.448146 4:0.586426 5:0.599033 6:0.112481
1 1:0.406015 2:0.411721 3:0.588133 4:0.757176 5:0.462532 6:0.196860
-1 1:0.131868 2:0.432938 3:0.614296 4:0.711778 5:0.178528 6:0.217912
1 1:0.489093 2:0.393096 3:0.568940 4:0.744675 5:0.527169 6:0.590553
-1 1:0.077703 2:0.226890 3:0.408387 4:0.523369 5:0.837690 6:0.454314

    If you’re still confused about the input format, use the script checkdata.py. It’s located in the libsvm-3.12/tools directory (relative to your libsvm installation) and can explain errors in formatting if any exist.

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