A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Object classification at the Nearby Supernova Factory
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
doi:10.1002/asna.200710932
fatcat:zsj2dhlf7rgcdn7y4gxwk4ll5q