How does the Self-Learning Analytics Engine learn?
Netuitive’s patented Self-Learning Analytics Engine uses multivariate correlation and regression analysis algorithms, coupled with self-learning and adaptive capabilities, and a multitude of proprietary and patented statistical heuristics to process data in real-time. This ability is complemented by its rapid learning capability to adapt to sudden changes. Netuitive’s multivariate correlation analysis algorithm automatically learns, identifies and understands how two or more variables, or performance metrics, co-vary in the natural environment. Correlation analysis techniques enable the engine to self-discover and study the relationships between variables. It understands how one metric relates to the variability of another. In addition, Netuitive uses multivariate regression analysis techniques to describe the numerical relationships between performance metrics. Whereas correlation analysis intuitively surmises the relationship strength between two metrics, regression analysis provides
