Salford Systems delivers a portfolio of products capable of traditional descriptive analytics and predictive analytics. What distinguishes this company is the lack of hype around the technology it offers and a willingness to discuss the pitfalls and traps associated with predictive analytics – which ironically is a prerequisite for successful analytics. The SPM Salford Predictive Modeler supports both traditional descriptive and predictive analytics. CART (Classification and Regression Tree) supports classification and the discovery of hidden relationships between attributes. It embodies a number of proprietary methods and patented extensions to the original work done in the eighties.
TreeNet is something of a black box and generates a plethora a reports for analysts to decipher the results of analysis. MARS (Multivariate Adaptive Regression Splines) produces regression models and is seen as a complement to CART. Finally Random Forests is best used on small(ish) data sets which might have many attributes, and includes prediction clusters and segment discoveries.
There are many layers within this product set, and skilled end-users will be able to generate powerful predictive models without a great deal of fuss. After this, it’s a matter of how deep you want to go. The technology has been used to address some of the most intractable machine learning problems, and has featured in many data mining competition wins.