Title of article :
Studies of boosted decision trees for MiniBooNE particle identification
Author/Authors :
Yang، نويسنده , , Hai-Jun and Roe، نويسنده , , Byron P. and Zhu، نويسنده , , Ji، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2005
Pages :
16
From page :
370
To page :
385
Abstract :
Boosted decision trees are applied to particle identification in the MiniBooNE experiment operated at Fermi National Accelerator Laboratory (Fermilab) for neutrino oscillations. Numerous attempts are made to tune the boosted decision trees, to compare performance of various boosting algorithms, and to select input variables for optimal performance.
Keywords :
Neutrino oscillations , Boosted decision trees , Artificial neural networks , Particle identification , MiniBooNE
Journal title :
Nuclear Instruments and Methods in Physics Research Section A
Serial Year :
2005
Journal title :
Nuclear Instruments and Methods in Physics Research Section A
Record number :
2204576
Link To Document :
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