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Introduction to Tree-Based Machine Learning

The following videos cover the underlying methods in the SPM® 8.2 Software Suite and provide demonstrations of each of the modeling engines.

Software Featured in the Videos:

  • SPM® 8.2 Software Suite
  • CART® Software
  • RandomForests® Software
  • TreeNet® Software
  • MARS® Software
  • RuleLearner™ Software
  • ISLE© Software
  • GeneralizedPathSeeker™ Software

Random Forests Supported Filetypes

Random Forests Supported Filetypes

The RandomForests® data-translation engine supports data conversions for more than 80 file formats, including popular statistical-analysis packages such as SAS® and SPSS®, databases such as Oracle and Informix, and spreadsheets such as Microsoft Excel and Lotus 1-2-3.

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Random Forests®

Random Forests

Breiman and Cutler’s Random Forests®:

Random Forests modeling engine 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' strengths are spotting outliers and anomalies in data, displaying proximity clusters, predicting future outcomes, identifying important predictors, discovering data patterns, replacing missing values with imputations, and providing insightful graphics.

Cluster and Segment:

Much of the insight provided by the Random Forests modeling engine is generated by methods applied after the trees are grown and include new technology for identifying clusters or segments in data as well as new methods for ranking the importance of variables. The method was developed by Leo Breiman and Adele Cutler of the University of California, Berkeley, and is licensed exclusively to Minitab.

Suited for Wide Datasets:

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 best suited for the analysis of complex data structures embedded in small to moderate data sets containing less than 10,000 rows but potentially millions of columns.

 

Software Demonstrations

resources software demonstrations

The videos contains the demonstrations of the techniques using the SPM® Software Suite. Software Featured in the Videos: SPM® Software Suite, CART® Software, Random Forests® Software, TreeNet® Software, MARS® Software, RuleLearner® Software, ISLE© Software, Generalized PathSeeker™ Software.

SPM® 8.2 Software Suite Demonstrations

Introduction to SPM® 8.2 Software & Exploring Data

 

A Fast Introduction to RandomForests® Software

 

CART® Software For Regression: Part I

 
This video provides an introduction to CART® software using the SPM® 8.2 Software Suite.

Introduction to MARS® Software for Regression

 

Introduction to TreeNet® Software for Binary Classification

 

Scoring New Data (Generate Predictions)

 
Table of Contents: click the button to the left of the full screen button (hover your mouse over the lower right hand corner of the video)

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