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| 
 Jet Flavour Tagging Howto | ||||||||
| Line: 77 to 77 | ||||||||
| <-- Jet theta angle cut (only the Glasgow NN trainer has this option) --> | ||||||||
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| < < | The neural nets are saved as XML files in gnets/and will be used for flavour tagging (next step). Noslciooutput is written at this time. | |||||||
| > > | The neural nets are saved as XML files in gnets/and will be used for flavour tagging (next step). Noslciooutput is written at this time. These neural networks can be downloaded from here:  gnets.tgz | |||||||
| Flavour Tagging | ||||||||
| Line: 129 to 129 | ||||||||
| For b-tagging, we've compared the plot produced by MakePurityVsEfficiencyRootPlotGla.Cand graphs drawn with the data tabulated inPurityEfficiencyOutput.txt, for 1, 2, 3 (corresponding to distinct neural networks) or any number of vertices (which we don't know yet how to interpret): | ||||||||
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| < < | Here's the script used to extract the numbers from PurityEfficiencyOutput.txt. | |||||||
| > > | Here's the script used to extract the numbers from PurityEfficiencyOutput.txt | |||||||
| Adding background | ||||||||
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| Added: | ||||||||
| > > | Training the neural nets with eeqq background addedWe can train another set of neural nets but adding this time eeqq background to the input. The resulting neural nets (25k signal + 25k background) are here: bnets.tgz. | |||||||
| Useful Links
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| 
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| > > | 
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  Copyright © 2008-2025 by the contributing authors. All material on this collaboration platform is the property of the contributing authors.
Copyright © 2008-2025 by the contributing authors. All material on this collaboration platform is the property of the contributing authors.