In the recent decade, several technologies have boomed up due to recent development in
many technologies. These technologies have changed the life of human being and are …

Nowadays, most real-world datasets suffer from the problem of imbalanced distribution of
data samples in classes, especially when the number of data representing the larger class …

Credit card fraud has negatively affected the market economic order, broken the confidence
and interest of stakeholders, financial institutions, and consumers. Losses from card fraud is …

Abstract The term “Internet of Things” is becoming increasingly popular and promising,
ushering in a new era of smarter connectivity across billions of gadgets. In the foreseeable …

Since last two decades, imbalanced data is becoming a hot topic to do research or to
determine meaningful results. One of the problems of machine learning and data mining …

Overcrowding of emergency department (ED) has put a strain on national healthcare
systems and adversely affected the clinical outcomes of critically ill patients. Early …

The look for methodologies that can make inferences from externally supplied data develop
broad hypotheses that are subsequently used to create forecasts concerning future events is …

Human visual target detection based on electroencephalography (EEG) signals has been
widely used to categorize target and non-target images, especially visual event-related …

Imbalanced datasets typically make prediction accuracy difficult. Most of the real-world data
are imbalanced in nature. The traditional classifiers assume a well-balanced class …

Due to the common use of electronic health databases in many healthcare services,
healthcare data are available for researchers in the classification field to make diseases' …