text classification : comparing classification reports
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11-12-2020 - |
解決
Okay so keeping it very short and precisely in context of your question-
Accuracy tells us, out of all the documents how many are classified correctly.
Precision tells us out of all documents which are predicted in a category, how often its correct.
Uni -gram- "nasa", "is" "space" , "agency" bi-gram- "nasa is", "space agency"
Now lets go over the numbers, in both the cases accuracy and precision doesn't have significant difference.
But as we can see bi-grams can give me much more information and hence can have better performance on unseen data. Try to test the model on unseen data/validation set and compare the difference.May be Try tri-grams etc also.
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