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Modeling in Revolution R Enterprise(TRA108)

Revolution Analytics, Inc.

Monday, June 9, 2014 at 8:00 AM - Friday, June 13, 2014 at 11:00 AM (PDT)

Modeling in Revolution R Enterprise(TRA108)

Ticket Information

Ticket Type Sales End Price Fee Quantity
General Admission Ended $599.00 $19.16

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Event Details


This training is divided into 3 session and each session is scheduled on a different day. The details of which are given below

06/9/2014 from 8AM - 11AM

06/11/2014 from 8AM - 11AM

06/13/2014 from 8AM - 11AM



This course is designed for Data Scientists who have mastered the basics of R and are interested in learning how to take advantage of the capabilities of Revolution R Enterprise for high performance analytics and modeling. This is a hands-on course filled with real data and examples, case studies, and in-class mini projects.

Introduction to Revolution R Enterprise for Predictive Modeling

One of the many advantages of Revolution R Enterprise is its ability to build predictive models on large enterprise-sized datasets. We will begin with an introduction to the predictive modeling functionality within Revolution R Enterprise.

  • Review of key Revolution R Enterprise programming concepts and data preparation
  • Algorithm and function overview
  • Standard function definitions and parameterization

Linear Regression Modeling and Evaluation

We will first introduce techniques for performing multivariate linear regression modeling available in Revolution R Enterprise.

  • Simple and multivariate regression models
  • Complex formulas and higher order terms.
  • Model review and evaluation including holdout evaluation.
  • Model selection using stepwise regression.
  • Predictions, model objects, and implementation.

Generalized Linear Models

Revolution R Enterprise includes capabilities to run bigdata GLM models, including logistic regression and tweedie models. We will introduce examples that show off these techniques:

  • Logistic regression model building and evaluation.
  • Additional forms for bigdata GLMs.
  • Predictions and implementation.

Data Mining using Trees and Forests

Revolution R Enterprise allows modelers to use decision trees and decision forests to build predictive models on big data.

  • Tree modeling functions and usage
  • Model evaluation and graphical review
  • Pruning.
  • Optimization of tree-building parameters.
  • Prediction and implementation.

Unsupervised Models and Other Techniques

Revolution R Enterprise includes additional advanced capabilities such as k-means clustering and principal components analysis for big data.

  • Introduction to clustering and principal components functions and techniques.
  • Review and evaluation of results.
  • Running simulations using rxExec




Have questions about Modeling in Revolution R Enterprise(TRA108)? Contact Revolution Analytics, Inc.


Monday, June 9, 2014 at 8:00 AM - Friday, June 13, 2014 at 11:00 AM (PDT)

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