CODEWITHSUNDEEP
machine-learningsvmlight
zvisofer
zvisofer

Reputation: 1368

SVM-Light displays corrupted precision/recall results

I run SVM-Light classifier but the recall/precision row it outputs seem to be corrupted:

Reading model...OK. (20 support vectors read)
Classifying test examples..100..200..done
Runtime (without IO) in cpu-seconds: 0.00
Accuracy on test set: 95.50% (191 correct, 9 incorrect, 200 total)
Precision/recall on test set: 0.00%/0.00%

What should I configure to get valid precision and recall?

Upvotes: 0

Views: 296

Answers (2)

user6110666
user6110666

Reputation: 11

Thank you greeness. your answer helped me too. To avoid this issue, make sure that the test and training datasets are chosen/grouped such that they have a fair mix of positive and negative values.

Upvotes: 1

greeness
greeness

Reputation: 16124

For example, if your classifier is always predicting "-1" -- the negative class; your test dataset, however, contains 191 "-1" and 9 "+1" as golden labels, you will get 191 of them correctly classified and 9 of them incorrect. 

True positives : 0        (TP)
True negatives : 191      (TN)
False negatives: 9        (FN)
False positives: 0        (FP)
Thus:
               TP             0
Precision = -----------  = --------- = undefined
             TP + FP         0 + 0

               TP             0
Recall    = -----------  = --------- = 0
             TP + FN        0 + 9

From the formula above, you know that as long as your TP is zero, your precision/recall is either zero or undefined.

To debug, you should output (for each test example) the golden label and the predicted label so that you know where the issue is.

Upvotes: 2

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