SPM & Minitab's Machine Learning Techniques
Minitab Statistical Software and Salford Predictive Modeler (SPM) are the ideal combination to analyze big data sets using machine learning techniques. The following image shows the interaction of Minitab and SPM.
CART® Modeling Engine
Classification and Regression trees
CART has revolutionized the field of advanced analytics and the current era of data science. CART is one of the most important tools in modern machine learning.
TreeNet® Modeling Engine
Gradient Boosting
TreeNet modeling engine is Salford Predictive Modeler's most flexible and powerful machine learning tool, responsible for at least a dozen prizes in major data mining competitions since its introduction in 2002. TreeNet adds the advantage of a degree of accuracy usually not attainable by a single model or by ensembles such as bagging or conventional boosting.
Random Forests® Modeling Engine
Breiman and Cutler's Random Forests
Random Forests provides insights into data by generating methods that are applied after the classification trees are grown. Furthermore, it includes new technology for identifying clusters or segments in data as well as new methods for ranking the importance of variables. Random Forests is a collection of many CART trees that are not influenced by each other when constructed. The sum of the predictions made from decision trees determines the overall prediction of the forest. Random Forests is great at analyzing complex data structures embedded in small to moderate data sets containing less than 10,000 rows but potentially millions of columns.
MARS® Modeling Engine
Automatic Non-linear Regression
MARS is ideal for users who prefer results similar to traditional regression while getting essential nonlinearities and interactions. The MARS methodology's approach to regression modeling effectively uncovers important data patterns and relationships that are difficult, if not impossible, for other regression methods to reveal.
ADDITIVE - Your Solution Partner
Machine Learning, Datamining und Big Data projects are a rather complex matter, which afford the use of many different techniques to get results in the end. These must be evaluated before a decision can be made, if the results represent a real solution because not every result is correct.
Contact our team of in-house consulting experts to see how they can help you build practical data mining solutions via email to