mva:mva
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| mva:mva [2016/08/06 12:43] – [Parameters to tune] iwn | mva:mva [2023/06/01 13:29] (current) – [Other information] iwn | ||
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| Line 8: | Line 8: | ||
| * [[https:// | * [[https:// | ||
| * [[https:// | * [[https:// | ||
| + | * [[https:// | ||
| When using the neural netwerk method MLP, you might need ROOT 5.34.0.0 or newer, to have larger buffer for the xml reader, for example: | When using the neural netwerk method MLP, you might need ROOT 5.34.0.0 or newer, to have larger buffer for the xml reader, for example: | ||
| - | < | + | < |
| . / | . / | ||
| </ | </ | ||
| - | |||
| Line 20: | Line 20: | ||
| To run the MVA in python on a signal tree '' | To run the MVA in python on a signal tree '' | ||
| - | < | + | < |
| from ROOT import TFile, TTree, TMVA, TCut | from ROOT import TFile, TTree, TMVA, TCut | ||
| f_out = TFile(" | f_out = TFile(" | ||
| Line 34: | Line 34: | ||
| </ | </ | ||
| - | In the empty quote marks you can add cuts or options. More information on can be found on the [[https:// | + | In the empty quote marks you can add cuts or options. More information on can be found in section 3.1 in the [[http:// |
| Then you can book multiple methods like the BDT and MLP for different parameters: | Then you can book multiple methods like the BDT and MLP for different parameters: | ||
| - | < | + | < |
| factory.BookMethod( TMVA.Types.kBDT, | factory.BookMethod( TMVA.Types.kBDT, | ||
| factory.BookMethod( TMVA.Types.kBDT, | factory.BookMethod( TMVA.Types.kBDT, | ||
| Line 50: | Line 50: | ||
| Finally train, test and evaluate all the booked methods: | Finally train, test and evaluate all the booked methods: | ||
| - | < | + | < |
| factory.TrainAllMethods() | factory.TrainAllMethods() | ||
| factory.TestAllMethods() | factory.TestAllMethods() | ||
| Line 56: | Line 56: | ||
| f_out.Close() | f_out.Close() | ||
| </ | </ | ||
| - | |||
| Line 63: | Line 62: | ||
| The factory will output weights in a XML file you can use to apply to a tree that contains the same variable. | The factory will output weights in a XML file you can use to apply to a tree that contains the same variable. | ||
| - | < | + | < |
| reader = TMVA.Reader() | reader = TMVA.Reader() | ||
| vars = [ ] | vars = [ ] | ||
| Line 69: | Line 68: | ||
| vars.append(array(' | vars.append(array(' | ||
| reader.AddVariable(name, | reader.AddVariable(name, | ||
| - | reader.BookMVA(TMVAClassification.weights.xml" | + | reader.BookMVA("TMVAClassification.weights.xml" |
| for i in range(len(config.varNames)): | for i in range(len(config.varNames)): | ||
| tree.SetBranchAddress(config.varNames[i], | tree.SetBranchAddress(config.varNames[i], | ||
| Line 89: | Line 88: | ||
| * '' | * '' | ||
| * '' | * '' | ||
| - | * '' | + | * '' |
| * '' | * '' | ||
| Line 107: | Line 106: | ||
| * [[https:// | * [[https:// | ||
| * [[mva: | * [[mva: | ||
| + | * [[https:// | ||
| + | |||
| + | |||
| + | ===== Other information ===== | ||
| + | |||
| + | * The working principles of a [[https:// | ||
| + | * [[https:// | ||
| + | * TMVA BibTex reference: | ||
| + | <code latex> | ||
| + | @article{TMVA, | ||
| + | title = {TMVA: Toolkit for Multivariate Data Analysis}, | ||
| + | author | ||
| + | | ||
| + | von Toerne, Eckhard and Voss, Helge}, | ||
| + | journal | ||
| + | volume | ||
| + | year = {2007}, | ||
| + | month = {Mar}, | ||
| + | pages = {040}, | ||
| + | url = {http:// | ||
| + | reportNumber | ||
| + | eprint | ||
| + | archivePrefix = {arXiv}, | ||
| + | primaryClass | ||
| + | SLACcitation | ||
| + | } | ||
| + | </ | ||
mva/mva.1470480198.txt.gz · Last modified: 2016/08/06 12:43 by iwn
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