Cost-sensitive learning is a popular paradigm to address class-imbalance learning (CIL) problem.Traditional cost-sensitive learning approaches always solve CIL problem by assigning a constant higher training error penalty for all minority instances than that of majority Glass Ornament instances, but ignore the significance of location information.T
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Knowledge discovery Pillow Protectors in big data is one of the most important applications of computing machinery today.Search is essential part of all such procedures.Search algorithms must be extremely efficient, but at the same time knowledge discovery procedures must not produce too many false positives or false negatives.False positives requi