Object classification at the Nearby Supernova Factory

S. Bailey, C. Aragon, R. Romano, R. C. Thomas, B. A. Weaver, D. Wong
2008 Astronomical Notes - Astronomische Nachrichten  
We present the results of applying new object classification techniques to the supernova search of the Nearby Supernova Factory. In comparison to simple threshold cuts, more sophisticated methods such as boosted decision trees, random forests, and support vector machines provide dramatically better object discrimination: we reduced the number of nonsupernova candidates by a factor of 10 while increasing our supernova identification efficiency. Methods such as these will be crucial for
more » ... g a reasonable false positive rate in the automated transient alert pipelines of upcoming large optical surveys.
doi:10.1002/asna.200710932 fatcat:zsj2dhlf7rgcdn7y4gxwk4ll5q