SPM
Salford Predicitve Modeler® 8
MACHINE LEARNING AND PREDICTIVE ANALYTICS SOFTWARE
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.
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.
Introducing Salford Predictive Modeler® 8
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.
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.
Ready for a demonstration of Minitab Statistical Software?
Introduction to Tree-Based Machine Learning
Section 1: Regression (quantitative target)
Learn the basics of Minitab's data mining software.
Introduction to CART Decision Trees for Regression
How to Write a Decision Tree (CART®) as an Equation
How are Variable Interactions Modeled in Decision Trees (CART®)?
Introduction to Random Forests for Regression
Introduction to Stochastic Gradient Boosting for Regression
Recommendation: Before watching this video, watch "Introduction to CART® decision Trees for Regression"
Introduction to MARS Nonlinear Regression Splines
Recommendation: Before watching this video, watch "Introduction to CART® decision Trees for Regression
Introduction to Tree-Based Machine Learning
Section 2: Classification (categorical target)
Introduction to CART Decision Trees for Classification
Introduction to Random Forests for Classification
Recommendation: Before watching this video, watch "Introduction to CART Decision Trees for Classification
Introduction to Stochastic Gradient Boosting for Classification
Recommendation: Before watching this video, watch "Introduction to CART Decision Trees for Classification"