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| mva:mva [2023/06/01 13:14] – [Other information] iwn | mva:mva [2023/06/01 13:29] (current) – [Other information] iwn |
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| * [[https://aholzner.wordpress.com/2011/08/27/a-tmva-example-in-pyroot/|TMVA in PyRoot tutorial]] | * [[https://aholzner.wordpress.com/2011/08/27/a-tmva-example-in-pyroot/|TMVA in PyRoot tutorial]] |
| * [[mva:mvaexample|This python example]] shows how you can run over multiple trees and different sets of variables. It also includes functions to apply the MVA output to trees and make background rejection vs. signal efficiency plots and correlation plots. | * [[mva:mvaexample|This python example]] shows how you can run over multiple trees and different sets of variables. It also includes functions to apply the MVA output to trees and make background rejection vs. signal efficiency plots and correlation plots. |
| | * [[https://root.cern/doc/master/group__tutorial__tmva.html|ROOT official TMVA tutorials]] |
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| ===== Other information ===== | ===== Other information ===== |
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| * The working principles of a [[https://www.physik.uzh.ch/~grazzini/teaching/higgsnotes/lecture6.pdf|neural network]] and a [[https://www.physik.uzh.ch/~grazzini/teaching/higgsnotes/lecture10.pdf|BDT]] are visually explained in the UZH's [[https://www.physik.uzh.ch/~grazzini/teaching/higgs.html|Higgs Physics course]] | * The working principles of a [[https://www.physik.uzh.ch/~grazzini/teaching/higgsnotes/lecture6.pdf|neural network]] and a [[https://www.physik.uzh.ch/~grazzini/teaching/higgsnotes/lecture10.pdf|BDT]] are visually explained in the UZH's [[https://www.physik.uzh.ch/~grazzini/teaching/higgs.html|Higgs Physics course]] by Mauro Donegà. |
| * [[https://arogozhnikov.github.io/2016/07/05/gradient_boosting_playground.html|Gradient Boosting Interactive Playground]] with interactive visuals | * [[https://arogozhnikov.github.io/2016/07/05/gradient_boosting_playground.html|Gradient Boosting Interactive Playground]] with interactive visuals |
| * TMVA BibTex reference: | * TMVA BibTex reference: |
