RecoParticleFlow-PFProducer/MVAnalysis_MLP.weights.txt at master · cms-data/RecoParticleFlow-PFProducer · GitHub

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#GEN -*-*-*-*-*-*-*-*-*-*-*- general info -*-*-*-*-*-*-*-*-*-*-*-

Method : MLP
Creator: cbern
Date   : Wed Sep 19 14:32:24 2007
Host   : Linux pcmsw46.cern.ch 2.6.18-1.2849_1.fc6.cubbi_suspend2 #1 SMP Mon Nov 13 11:02:05 EST 2006 i686 i686 i386 GNU/Linux
Dir    : /home/cbern/CMS/TMVA
Training events: 2000


#OPT -*-*-*-*-*-*-*-*-*-*-*-*- options -*-*-*-*-*-*-*-*-*-*-*-*-

# Set by User:
V: False [verbose flag]
NCycles: 200 [Number of training cycles]
HiddenLayers: "N+1,N" [Specification of the hidden layers]
TestRate: 5 [Test for overtraining performed at each #th epochs]
# Default:
D: False [use-decorrelated-variables flag (for backward compatibility)]
Preprocess: "None" [Variable Decorrelation Method]
PreprocessType: "Signal" [Use signal or background for Preprocess]
H: False [help flag]
Normalize: True [Normalize input variables]
NeuronType: "sigmoid" [Neuron activation function type]
NeuronInputType: "sum" [Neuron input function type]
TrainingMethod: "BP" [Train with Back-Propagation (BP) or Genetic Algorithm (GA) (takes a LONG time)]
LearningRate: 0.02 [NN learning rate parameter]
DecayRate: 0.01 [Decay rate for learning parameter]
BPMode: "sequential" [Back-propagation learning mode: sequential or batch]
BatchSize: -1 [Batch size: number of events/batch, only set if in Batch Mode, -1 for BatchSize=number_of_events]
##


#VAR -*-*-*-*-*-*-*-*-*-*-*-* variables *-*-*-*-*-*-*-*-*-*-*-*-

NVar 3
                  eECAL/pTrack                eECAL_D_pTrack    'F'    [0.00297716,5.57195]
                      chi2ECAL                      chi2ECAL    'F'    [0.00071052,49.9922]
                       ptTrack                       ptTrack    'F'    [1.19972,224.227]


#WGT -*-*-*-*-*-*-*-*-*-*-*-*- weights -*-*-*-*-*-*-*-*-*-*-*-*-

Weights
(layer0,neuron0)-(layer1,neuron0): 3.41468
(layer0,neuron0)-(layer1,neuron1): 4.06707
(layer0,neuron0)-(layer1,neuron2): 0.977804
(layer0,neuron0)-(layer1,neuron3): 0.781785
(layer0,neuron1)-(layer1,neuron0): 1.21585
(layer0,neuron1)-(layer1,neuron1): 0.762225
(layer0,neuron1)-(layer1,neuron2): -1.41583
(layer0,neuron1)-(layer1,neuron3): 1.18808
(layer0,neuron2)-(layer1,neuron0): 1.69654
(layer0,neuron2)-(layer1,neuron1): 1.43885
(layer0,neuron2)-(layer1,neuron2): -0.602632
(layer0,neuron2)-(layer1,neuron3): -1.35783
(layer0,neuron3)-(layer1,neuron0): 2.48269
(layer0,neuron3)-(layer1,neuron1): 2.51145
(layer0,neuron3)-(layer1,neuron2): -0.915172
(layer0,neuron3)-(layer1,neuron3): 1.88767
(layer1,neuron0)-(layer2,neuron0): 3.03507
(layer1,neuron0)-(layer2,neuron1): 0.583081
(layer1,neuron0)-(layer2,neuron2): -0.098933
(layer1,neuron1)-(layer2,neuron0): 3.88477
(layer1,neuron1)-(layer2,neuron1): 1.40102
(layer1,neuron1)-(layer2,neuron2): 1.64582
(layer1,neuron2)-(layer2,neuron0): 2.30704
(layer1,neuron2)-(layer2,neuron1): -0.841536
(layer1,neuron2)-(layer2,neuron2): -1.28704
(layer1,neuron3)-(layer2,neuron0): 0.966986
(layer1,neuron3)-(layer2,neuron1): 0.00223062
(layer1,neuron3)-(layer2,neuron2): -1.59379
(layer1,neuron4)-(layer2,neuron0): -1.88828
(layer1,neuron4)-(layer2,neuron1): 2.12644
(layer1,neuron4)-(layer2,neuron2): 1.10617
(layer2,neuron0)-(layer3,neuron0): 2.69837
(layer2,neuron1)-(layer3,neuron0): 0.751617
(layer2,neuron2)-(layer3,neuron0): -0.455939
(layer2,neuron3)-(layer3,neuron0): -2.06181