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Data organized into discrete categories or *classes* may present problems for certain analyses if the number of observations ($n$) belonging to each class is not constant across classes. Classes with unequal $n$ are *unbalanced*.
8
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Handling unbalanced data using SMOTE - no big difference?
I have a classification problem with 2 classes. I have nearly 5000 samples, each of which is represented as vector with 570 features. The positive class samples are nearly 600. Meaning, I have a 1:8 r …
11
votes
2
answers
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Is f-measure synonymous with accuracy?
I understand that f-measure (based on precision and recall) is an estimate of how accurate a classifier is. Also, f-measure is favored over accuracy when we have an unbalanced dataset. I have a simple …