Artificial intelligence (AI) is receiving increasing attention in business and society. In
banking, the first applications of AI were successful; however, AI is mainly applied in …

The need for controlling and effectively managing credit risk has led financial institutions to
excel in improving techniques designed for this purpose, resulting in the development of …

Boosting and bagging are two widely used ensemble methods for classification. Their
common goal is to improve the accuracy of a classifier combining single classifiers which …

An intelligent framework is necessary to detect and analyze bearing defects in rotating
machinery to prevent unexpected downtime and achieve performance per Industry 4.0 …

During the last years, hybrid models have proven to be a promising approach for the design
of classification systems for the forecasting of bankruptcy. In the present research we …

The level of modeling sophistication in financial services has increased considerably over
the years. Nowadays, the complexity of financial problems and the vast amount of data …

Sexual cyberbullying is becoming a serious problem in today's society. In the workplace, this
issue is more complex because of the power imbalance between potential perpetrators and …

Debt collection via call centers is an important operation in many business domains since it
can significantly improve a firm's financial status by turning bad receivables into normal cash …

An essential guide to two burgeoning topics in machine learning–classification trees and
ensemble learning Ensemble Classification Methods with Applications in R introduces the …

Two algorithms for building classification trees, based on Tsallis and Rényi entropy, are
proposed and applied to customer churn problem. The dataset for modeling represents …