Salford Predictive Modeler
MARS® - Multivariate Adaptive Regression Splines
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Multivariate Adaptive Regression Splines
MARS® is ideal for those users who prefer results in a form similar to traditional regression while capturing essential nonlinearities and interactions. Effectively uncovers important data pattern and relationships that are difficult, for other regression methods to reveal. MARS methodology’s approach permits the modelling engine to trace out any pattern detected in the data. The MARS modelling engine builds its model by a series of straight lines with each allowed its own slope.
High-Quality Regression
and Classification
We can find many applications of MARS in an organisation. It is designed to predict numeric outcomes such as the average fuel consumption by a machine or an average monthly bill of a mobile phone customer. MARS is also capable of producing high-quality classification models for a yes/no outcome.
High-Performance
Results
Areas where the MARS engine has exhibited very high-performance results include forecasting electricity demand for power generating companies, relating customer satisfaction scores to the engineering specifications of products, and presence/absence modelling in geographical information systems (GIS).
Salford Predictive Modeler® 8
Minitab’s Integrated Suite of Machine Learning & Predictive Analytics Software
CART®
CART® (Classification And Regression Trees) is one of the most important tools in modern data mining. It provides the ultimate classification tree that has revolutionized the field of advanced analytics & data science.
MARS®
MARS® (Multivariate Adaptive Regression Splines) methodology’s approach to regression modeling effectively uncovers important data patterns & relationships that are difficult for other regression methods to reveal.
TreeNet®
TreeNet® demonstrates remarkable performance for both regression and classification. It is the most flexible and powerful data mining tool, capable of consistently generating extremely accurate models.
Random Forests®
Random Forests® helps to spot outliers & anomalies in data, display proximity clusters, predict future outcomes, identify important predictors, discover data patterns & provide insightful graphics.
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