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Imbalanced data classification

What is it about?

Class imbalance is a common problem and it occurs when instances of negative/major class is significantly more than the positive/minor class. The class with scanty instances are always a problem of interest. The conventional learning algorithms are more lenient towards predicting major classes because general rules are more preferred than the specific rules required for predicting the samples from minority class.

Why is it important?

It is observed from the statistical measure that the hybrid over sampled method demonstrated a significant improvement over other combination of the sampling methods for the imbalanced problems.

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The following have contributed to this page:
sujata dash and Rabi Behera
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