JSM 2014 Home
Online Program Home
My Program

Abstract Details

Activity Number: 409
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 2:00 PM to 2:45 PM
Sponsor: Section on Nonparametric Statistics
Abstract #314077
Title: Novel Methods to Identify and Estimate Interactions via Random Forest
Author(s): Arturo Valdivia*+
Companies:
Keywords: Random Forest ; Interactions ; Statistical Learning ; Data Mining
Abstract:

This work proposes two heuristic methods to capture characteristics of data using the ensemble learning method of random forest. The study develops two novel interaction measures. The first measure is constructed to identify interactions in a general setting where a model specification is not assumed in advance. The second measure is built to identify and estimate interactions when the model specification is assumed to be linear. Both measures are unique in their construction; they take into account not only the outcome values, but also the internal structure of the trees in a random forest. In a simulation study, under a variety of conditions, the proposed measures are found to identify and estimate higher-order interactions. Potential applications of these methods are also presented.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2014 program




2014 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Professional Development program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.