Predictive Modelling

The complexity of business environments today means that identifying rules and connections between different features is often beyond human processing capabilities.

Predictive modelling schema

The predictive modelling allows us to reveal hidden relationships between features and ultimately to better understand any problem analysed, as well as to build mechanisms of simulation, prediction or estimation.

Generally speaking such models, interlinking a set of known attributes and relating them to another attribute, can be used to find the values of variables that we cannot measure. We may not be able to measure a variable outright because of technical or economical issues. In some cases the attributes are predicted values.

SDART applies its expertise in several fields for example Finance, Insurance, the Health Service and Engineering. In Finance a common task is to find the relationship between movements of stock market prices or indices and their future effects. The essential question for Insurance is how an insured party’s profile predicts potential loses, and could be used to calculate an appropriate insurance fee. The Health Services deploy mathematical models to estimate the necessity of costly specialised medical examinations and tests for patients. The Engineering applications of mathematical modelling include the analysis of machinery’s condition with relation to measurable signals (power consumption, vibrations, etc.).

(see how to implement it our Data Mining guide)

Data Mining Service

SDART offers a professional service helping with a detailed understanding of Data Mining methods and Predictive Modelling algorithms. For more information please contact one of our experts. (see our Data Mining service)