The class imbalance problem in two-class data sets is one of the most important problems. When examples of one class in a training data set vastly outnumber examples of the other class, standard machine learning algorithms tend to be overwhelmed by the majority class and ignore the minority class. There are several algorithms to alleviate the problem of class imbalance in literature. In this pa...

Classification of sheep behaviour from a sequence tri-axial accelerometer data has the potential to enhance management. Sheep is inherently imbalanced (e.g., more ruminating than walking) resulting in underperforming classification for minority activities which hold importance. Existing works have not addressed class imbalance and use traditional machine learning techniques, e.g., Random Forest...

The learning from imbalanced data is a deeply studied problem in standard classification and, in recent times, also in multilabel classification. A handful of multilabel resampling methods have been proposed in late years, aiming to balance the labels distribution. However these methods have to face a new obstacle, specific for multilabel data, as is the joint appearance of minority and majorit...

To identify the chromosomal aberrations associated with the progression of liver cancer, we applied expression imbalance map analysis to gene expression data from 31 hepatocellular carcinomas and 19 noncancerous tissues. Expression imbalance map analysis, which detects mRNA expression imbalance correlated with chromosomal regions, showed that expression gains of 1q21-23 (74%), 8q13-21 (48%), 12...

abstract background: while nursing workload is a worldwide challenge, less attention has been given to the determining factors. understanding these factors is important and could help nursing managers to provide suitable working environment and to manage the adverse outcomes of nursing workload. the aim of this study was to discover nurses’ experiences of determinant factors of their workload. ...

We study the trading of individual investors using transaction data and identifying buyeror seller-initiated trades. We document four results: (1) Small trade order imbalance correlates well with order imbalance based on trades from retail brokers. (2) Individual investors herd. (3) When measured annually, small trade order imbalance forecasts future returns; stocks heavily bought underperform ...

In this paper we discuss the effects of non-algorithmic load imbalance for three synchronization structures which appear in different algorithms using domain decomposition methods for solving PDE's on a hypercube machine. The synchronization structures are determined from the conditions related to the partitioning of a hypercube. To characterize the load imbalance effects we introduce a factor ...