Speaker
Dr
Ilya Narsky
(California Institute of Technology)
Description
SPR implements various tools for supervised learning such as boosting (3 flavors),
bagging, random forest, neural networks, decision trees, bump hunter (PRIM),
multi-class learner, logistic regression, linear and quadratic discriminant analysis,
and others. Presented at CHEP 2006, SPR has been extended with several important
features since then. The package has been stripped of CLHEP dependency, equipped with
autotools and posted at Sourceforge for distribution under general public license:
http://sourceforge.net/projects/statpatrec/ . It is now a standalone package with an
optional dependency on Root for data input/output. Several new methods have been
included in the package. SPR is now capable of boosting and bagging an arbitrary
sequence of included classifiers allowing the user to explore a broad range of
classifier combinations. This talk is meant to summarize recent updates to the
package and review recent applications of the package to physics analysis. More info
on the project is available from http://www.hep.caltech.edu/~narsky/spr.html .
Primary author
Dr
Ilya Narsky
(California Institute of Technology)
