Title: Performance study of Boosted Decision Trees in a Gravitational Wave Burst Search
Authors: Satya Mohapatra, Sebastian Fischetti, Laura Cadonati

We explore the implementation of multivariate classification analysis in 
gravitational wave burst searches, to separate signals from background.
We focus on the Boosted Decision Tree algorithm and the coincidence between 
three interferometers (two of which co-located) as applied in the LSC S5 burst 
analysis with the Omega pipeline. The Boosted Decision Tree algorithm, from the 
ROOT TMVA package, is applied to bandwidth, duration, H1H2 coherent energy, H1H2
correlated energy and L1 normalized energy.