The Imbalanced class problem is a recent challenge in data mining. A dataset is said to be imbalance when their classification categories are not properly mentioned, and the class which has fewer instances as compare to other classes is of more interest from the point of view of the learning task. Here we study about the various factors that influence the datasets and leads to imbalance the dataset like as Features selection, classification of imbalance datasets. Here in this paper, we also discussed about the various sampling methods utilize for dataset balancing and for getting measurable performance.
No takes yet. Share an insight, caveat, or question.
A 2017 study studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: