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A * preceding a session name means that the session is an applied session.
A ! preceding a session name means that the session reflects the JSM meeting theme.
A * preceding a session name means that the session is an applied session.
A ! preceding a session name means that the session reflects the JSM meeting theme.
Activity Details
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| CE_27T | Wed, 8/6/2014, 8:00 AM - 9:45 AM | W-Douglass | |
| Introduction to Data Mining with CART Classification and Regression Trees — Professional Development Computer Technology Workshop | |||
| ASA , Salford Systems | |||
| This Tutorial is intended for the applied statistician wanting to understand and apply the CART Classification and Regression Trees methodology for tree-structured nonparametric data analysis. The emphasis will be on practical data analysis and data mining involving classification and regression. All concepts will be illustrated using real-world examples. The course will begin with an intuitive introduction to tree-structured analysis: what it is, why it works, why it is non-parametric and model-free, advantages in handling of all types of data including missing values and categorical. Working through examples, we will review how to read the CART Classification and Regression Tree output and how to set up basic analyses. This session will include performance evaluation of CART trees and will cover ways to search for possible improvements of the results. Once a basic working knowledge of CART has been mastered, the tutorial will focus on critical details essential for advanced CART applications including: choice of splitting criteria, choosing the best split, using prior probabilities to shape results, refining results with differential misclassification costs, the meaning of cross validation, tree growing and tree pruning. The course will conclude with some discussion of the comparative performance of CART versus other computer-intensive methods such as artificial neural networks and statistician-generated parametric models. All attendees will receive 6 months access to fully functional versions of the the SPM Salford Predictive Modeler software suite. No prerequisites. | |||
| Instructor(s): Mikhail Golovnya, Salford Systems | |||
2014 JSM Online Program Home
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