Title of article :
Cascade training technique for particle identification
Author/Authors :
Liu، نويسنده , , Yong and Stancu، نويسنده , , Ion، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2007
Pages :
7
From page :
315
To page :
321
Abstract :
The cascade training technique which was developed during our work on the MiniBooNE particle identification has been found to be a very efficient way to improve the selection performance, especially when very low background contamination levels are desired. The detailed description of this technique is presented here based on the MiniBooNE detector Monte Carlo simulations, using both artificial neural networks and boosted decision trees as examples.
Keywords :
NEURAL NETWORKS , Computer data analysis , Neutrino oscillations
Journal title :
Nuclear Instruments and Methods in Physics Research Section A
Serial Year :
2007
Journal title :
Nuclear Instruments and Methods in Physics Research Section A
Record number :
2206676
Link To Document :
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