Ensembles of classifiers is a proven approach in machine learning with a wide variety of
research works. The main issue in ensembles of classifiers is not only the selection of the …

The world of banking requires a marketer to be able to reduce the risk of borrowing by
keeping his customers from occurring non-performing loans. One way to reduce this risk is …

Software defect prediction is a way to improve quality by finding and tracking defective
modules in the software which helps reduce costs during the software testing process. The …

Background Although carotid sonographic features have been used as predictors of
recurrent stroke, few large-scale studies have explored the use of machine learning analysis …

Class imbalance is a common problem in classification tasks. The learning schemes of most
classification algorithms tend to optimize the overall accuracy, and thus, identification of …

Amongst all types of cancer, breast cancer has become one of the most common cancers in
the UK threatening millions of people's health. Early detection of breast cancer plays a key …

Traditional practices of education, medicine, and economics often use collective expert
methods to find acceptable solutions to complex issues. The computer model of such …

Background and objective Preoperative diagnosis of parathyroid carcinoma (PC) is critical
for the determination of the scope of surgical intervention. Nowadays, specific diagnostic …

In domain of data mining, learning from imbalanced class distribution datasets is a
challenging problem for conventional classifiers. The class imbalance exists when the …

The movie industry is one of the largest and most influential sectors of any community. Each
movie in the industry consists of different elements such as actors, directors, preparation …