Because accuracy matters
The Salford Predictive Modeler® (SPM) software suite is a highly accurate and ultra-fast platform for developing predictive, descriptive, and analytical models.
Introducing Salford Predictive Modeler® 8
Minitab's Integrated Suite of Machine Learning Software
The Salford Predictive Modeler® software suite includes the CART®, MARS®, TreeNet®, Random Forests® engines, as well as powerful new automation and modeling capabilities not found elsewhere.
The SPM software suite’s data mining technologies span classification, regression, survival analysis, missing value analysis, data binning and clustering/segmentation. SPM algorithms are considered to be essential in sophisticated data science circles.
CART®
SPM’s CART® modeling engine is the ultimate classification tree that has revolutionized the field of advanced analytics, and inaugurated the current era of data science.
Random Forests®
Random Forests® is a modeling engine that leverages the power of multiple alternative analyses, randomization strategies, and ensemble learning.
MARS®
The MARS® modeling engine is ideal for users who prefer results in a form similar to traditional regression while capturing essential nonlinearities and interactions.
TreeNet®
TreeNet® Gradient Boosting is SPM’s most flexible and powerful data mining tool, capable of consistently generating extremely accurate models.
Brainpower
70+ pre-packaged automation scenarios inspired by the way leading model analysts structure their work.
Efficiencies
Tools to relieve gruntwork, allowing the analyst to focus on the creative aspects of model development.
Enhanced Algorithms
Regression, Classification, and Logistic Regression enhanced to support massive datasets.
Improvements
New features for our core tools, based on user feedback and advances in data science.
Bridging-the-gap
Between the leading edge academic thinking of Jerome Friedman and Leo Breiman and real-world applications.
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Our University Program provides the SPM®, CART®, MARS®, TreeNet® , and Random Forests® modeling engines at significantly-reduced licensing fees to the educational community.
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70+ pre-packaged scenarios, basically experiments, inspired by how leading model analysts structure their work.
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