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Machine Learning and Predictive Analytics Software

Salford-Predictive-Modeler

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.

The SPM software suite‘s automation accelerates the process of model building by conducting substantial portions of the model exploration and refinement process for the analyst. We package a complete set of results from alternative modeling strategies for easy review.

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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.

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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.

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TreeNet®

TreeNet® Gradient Boosting is SPM’s most flexible and powerful data mining tool, capable of consistently generating extremely accurate models.

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Random Forests®

Random Forests® is a modeling engine that leverages the power of multiple alternative analyses, randomization strategies, and ensemble learning.

SPM® feature list

Brainpower

70+ pre-packaged automation scenarios inspired by the way leading model.

Improvements

New features for our core tools, based on user feedback and advances in data science.

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.

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