KDnuggets Home » News :: 2013 :: Mar :: Webcasts :: Salford: The Evolution of Regression Free, Hands-on Webinar Series, Mar 15, 29, Apr 12 ( 13:n07 )

Salford: The Evolution of Regression
Free, Hands-on Webinar Series, Mar 15, 29, Apr 12


Regression is a key analytics tool - learn the latest in upcoming free webinar series: The Evolution of Regression - From Classical Linear Regression to Modern Ensembles



You can get the slides if you missed Part 1 of
"The Evolution of Regression Modeling" webinar series,
and you can still join for Parts 2, 3, & 4 - Space is Limited!

Register for Evolution of Regression parts 2,3,4
www1.gotomeeting.com/register/500959705

Download (optional) a free evaluation of the SPM software suite v7.0 (used in the hands-on components of the webinar). As a webinar participant you will qualify for a 60-Day Evaluation of the software at no charge

Number of predictors in a modelCourse Outline:
Overcoming Linear Regression Limitations

Regression is one of the most popular modeling methods, but the classical approach has significant problems. This webinar series addresses these problems.

  • Are you working with larger datasets?
  • Is your data challenging?
  • Does your data include missing values, nonlinear relationships, local patterns and interactions?

This webinar series is for you! We will cover improvements to conventional and logistic regression, and will include a discussion of classical, regularized, and nonlinear regression, as well as modern ensemble and data mining approaches. This series will be of value to any classically trained statistician or modeler.

Part 2: March 15, 10-11am PT, 1-2 pm ET
Hands-on demonstration of concepts discussed in Part 1 (Classical Regression, Logistic Regression, Regularized Regression: GPS Generalized Path Seeker, Nonlinear Regression: MARS Regression Splines)

  • Step-by-step demonstration
  • Datasets and software available for download
  • Instructions for reproducing demo at your leisure
  • For the dedicated student: apply these methods to your own data (optional)

Part 3: March 29, 10-11am PT, 1-2pm ET - Regression methods discussed
*Part 1 is a recommended pre-requisite

  • Nonlinear Ensemble Approaches: TreeNet Gradient Boosting; Random Forests; Gradient Boosting incorporating RF
  • Ensemble Post-Processing: ISLE; RuleLearner

Part 4: April 12, 10-11am PT, 1-2pm ET - Hands-on demonstration of concepts discussed in Part 3

  • Step-by-step demonstration
  • Datasets and software available for download
  • Instructions for reproducing demo at your leisure
  • For the dedicated student: apply these methods to your own data (optional)


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