ABSTRACT
Business intelligence measurements depend on a variety of statistical advanced technologies used to enable the collection, analysis, and dissemination of internal and external business information. The key goal of business intelligence is to draw a well-informed business decision. Statistical machine learning-based business intelligence systems prioritize a comprehensive analysis to empower businesses. In kernel methods, the nonlinear feature map is given by a positive-definite kernel, which provides nonlinear methods for data analysis with efficient computation. In kernel methods, the nonlinear feature map is given by a positive-definite kernel , which provides nonlinear methods for data analysis with efficient computation. The standard industrial informatics are facing the challenges of processing complex business data. Business intelligence plays an important role to bridge the gap between enterprise systems and industrial informatics. In supervised machine learning tasks, switching regression is becoming an increasingly common component in the age of big business data.
