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Problem with learning and saving classifier without performing any testing #1
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Meka tried to do an evaluation in any case. And it ended up with an empty test set, and empty results. As a quick solution, I added a check if the train or test set is empty, then Meka does not evaluate and just trains on the full set. It is pushed it to the 1.9.1.-SNAPSHOT. But we might change the options, add a flag for evaluation or only training. |
That's a good point actually. Nice to have that fix, Joerg. Another quick On 29 February 2016 at 01:03, Joerg Wicker notifications@github.com wrote:
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Closing this issue mentioning that you can use the |
I am trying to learn a classifier and store it for the future without the need to test it at the time of classification. I am using the following command to make sure no splitting for test is done (without it meka reported test instance count larger than 0):
/usr/bin/java -cp "/home/niedakh/scikit/meka/meka-release-1.9.0/lib/*" meka.classifiers.multilabel.LC -W weka.classifiers.bayes.NaiveBayes -threshold 0 -verbosity 5 -split-percentage 100 -t ~/engine/scikit-multilearn/meka/data/scene-train.arff -d classifier.dump
I am receiving an error:
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