I've retrained it on 10,000 BMC sections and used this to classify 10,000 PMC sections.
These two section sets should be mutually exclusive. However i'm not sure they are, because PMC distributes BMC content. I'll have to look in to this overlap.
Anyway here is the result
Sect Corr Incor Precis Recall F-Measure
INTROD 2308 839 0.7334 0.8809 0.8004
METHOD 1927 503 0.793 0.9432 0.8616
RESULT 1311 218 0.8574 0.8023 0.829
DISCUS 2672 222 0.9233 0.7216 0.8101
Correct: 8218 proportion correct: 0.8218 percentage correct: 82.17999999999999
Incorrect: 1782 proportion incorrect: 0.1782 percentage incorrect: 17.82
724482msnot bad considering that when you train on all sections (over 300,000) then you get this for 10,000 classifications.
Sect Corr Incor Precis Recall F-Measure
INTROD 2166 804 0.7293 0.8794 0.7973
METHOD 2041 536 0.792 0.9281 0.8547
RESULT 1409 443 0.7608 0.8508 0.8033
DISCUS 2525 76 0.9708 0.6858 0.8038
Correct: 8141 proportion correct: 0.8141 percentage correct: 81.41000000000001
Incorrect: 1859 proportion incorrect: 0.1859 percentage incorrect: 18.59
585402ms
nice
