Class imbalance data usually suffers from data intrinsic properties beyond that of imbalance alone. The problem is intensified with larger levels of imbalance most commonly found in observational studies. Extreme cases of class imbalance are commonly found in many domains including fraud detection, mammography of cancer and post term births. These rare events are usually the most costly or have...

The I/O subsystem is becoming a major bottleneck in an increasing number of computer systems. To provide improved I/O performance, as well as to accommodate growing storage requirements, disk subsystems are increasing in size. A major hurdle to obtaining the performance available from these large disk subsystems is load imbalance, or disk skew. Dynamic data placement, the conventional load bala...

The I/O subsystem is becoming a major bottleneck in an increasing number of computer systems. To provide improved I/O performance, as well as to accommodate growing storage requirements, disk subsystems are increasing in size. A major hurdle to obtaining the performance available from these large disk subsystems is load imbalance, or disk skew. Dynamic data placement, the conventional load bala...

Class imbalance is one of the challenges of machine learning and data mining fields. Imbalance data sets degrades the performance of data mining and machine learning techniques as the overall accuracy and decision making be biased to the majority class, which lead to misclassifying the minority class samples or furthermore treated them as noise. This paper proposes a general survey for class im...