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However, in the case study of skewed distributions, results are highly deceiving since minority classes hold minimum effect on overall accuracy.
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Over_sampling of the minority classes help to improve the performance.
WHERE are classes held?
No classes held.
The remaining minority classes are arranged as per their respective status of lowest minority class having I.R. > 1.5.
On a highly imbalanced class distribution, it is particularly demanding to identify instances from minority classes.
On a highly imbalanced class distribution, it is particularly demanding to identify examples from minority classes.
Considering the minority classes were less than 1%, this is very promising.
A direct consequence is that minority classes cannot be well modeled, and the final performance decays.
And minority candidates hold office at unprecedented levels.
lowest minority class (for multi-class data sets).
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