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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*.
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Class imbalance in Supervised Machine Learning
There are many frameworks and approaches. This is a recurrent issue.
Examples:
Undersampling. Select a subsample of the sets of zeros such that it's size matches the set of ones. There is an obviou …