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Reference Guide
Functions | Variables
ClassificationKeras Namespace Reference

Functions

def normal (shape, name=None)
 

Variables

 background = data.Get('TreeB')
 
 data = TFile.Open('tmva_class_example.root')
 
 dataloader = TMVA.DataLoader('dataset')
 
 factory
 
 loss
 
 metrics
 
 model = Sequential()
 
 optimizer
 
 output = TFile.Open('TMVA.root', 'RECREATE')
 
 signal = data.Get('TreeS')
 

Function Documentation

◆ normal()

def ClassificationKeras.normal (   shape,
  name = None 
)

Definition at line 41 of file ClassificationKeras.py.

Variable Documentation

◆ background

ClassificationKeras.background = data.Get('TreeB')

Definition at line 27 of file ClassificationKeras.py.

◆ data

ClassificationKeras.data = TFile.Open('tmva_class_example.root')

Definition at line 25 of file ClassificationKeras.py.

◆ dataloader

ClassificationKeras.dataloader = TMVA.DataLoader('dataset')

Definition at line 29 of file ClassificationKeras.py.

◆ factory

ClassificationKeras.factory
Initial value:
1 = TMVA.Factory('TMVAClassification', output,
2  '!V:!Silent:Color:DrawProgressBar:Transformations=D,G:AnalysisType=Classification')
This is the main MVA steering class.
Definition: Factory.h:81

Definition at line 18 of file ClassificationKeras.py.

◆ loss

ClassificationKeras.loss

Definition at line 51 of file ClassificationKeras.py.

◆ metrics

ClassificationKeras.metrics

Definition at line 51 of file ClassificationKeras.py.

◆ model

ClassificationKeras.model = Sequential()

Definition at line 45 of file ClassificationKeras.py.

◆ optimizer

ClassificationKeras.optimizer

Definition at line 51 of file ClassificationKeras.py.

◆ output

ClassificationKeras.output = TFile.Open('TMVA.root', 'RECREATE')

Definition at line 17 of file ClassificationKeras.py.

◆ signal

ClassificationKeras.signal = data.Get('TreeS')

Definition at line 26 of file ClassificationKeras.py.