Processing polarizedReducedDeconvFisher.C... : Parsing option string: : ... "V" : The following options are set: : - By User: : V: "True" [Verbose flag] : - Default: : Color: "True" [Flag for coloured screen output (default: True, if in batch mode: False)] : Transformations: "I" [List of transformations to test; formatting example: "Transformations=I;D;P;U;G,D", for identity, decorrelation, PCA, Uniform and Gaussianisation followed by decorrelation transformations] : Correlations: "False" [boolean to show correlation in output] : ROC: "True" [boolean to show ROC in output] : Silent: "False" [Batch mode: boolean silent flag inhibiting any output from TMVA after the creation of the factory class object (default: False)] : DrawProgressBar: "True" [Draw progress bar to display training, testing and evaluation schedule (default: True)] : ModelPersistence: "True" [Option to save the trained model in xml file or using serialization] : AnalysisType: "Auto" [Set the analysis type (Classification, Regression, Multiclass, Auto) (default: Auto)] DataSetInfo : [tmvaFiles] : Added class "Signal" : Add Tree cutTree of type Signal with 188321 events DataSetInfo : [tmvaFiles] : Added class "Background" : Add Tree cutTree of type Background with 1544656 events Factory : Booking method: deconvFisher : Factory : Train all methods DataSetFactory : [tmvaFiles] : Number of events in input trees : : : Dataset[tmvaFiles] : Weight renormalisation mode: "EqualNumEvents": renormalises all event classes ... : Dataset[tmvaFiles] : such that the effective (weighted) number of events in each class is the same : Dataset[tmvaFiles] : (and equals the number of events (entries) given for class=0 ) : Dataset[tmvaFiles] : ... i.e. such that Sum[i=1..N_j]{w_i} = N_classA, j=classA, classB, ... : Dataset[tmvaFiles] : ... (note that N_j is the sum of TRAINING events : Dataset[tmvaFiles] : ..... Testing events are not renormalised nor included in the renormalisation factor!) : Number of training and testing events : --------------------------------------------------------------------------- : Signal -- training events : 94160 : Signal -- testing events : 94160 : Signal -- training and testing events: 188320 : Background -- training events : 772328 : Background -- testing events : 772328 : Background -- training and testing events: 1544656 : DataSetInfo : Correlation matrix (Signal): : --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- : deconvWaveformCuts.waveformPeakZScore[0] deconvWaveformCuts.waveformPeakZScore[1] deconvWaveformCuts.analyticPeakZScore[0] deconvWaveformCuts.analyticPeakZScore[1] deconvWaveformCuts.linearPolFrac[0] deconvWaveformCuts.linearPolFrac[1] deconvWaveformCuts.impulsivity[0] deconvWaveformCuts.impulsivity[1] deconvWaveformCuts.TIMdB[0] deconvWaveformCuts.TIMdB[1] deconvWaveformCuts.corrPeakZScore[0] deconvWaveformCuts.corrPeakZScore[1] deconvWaveformCuts.analyticCorrPeakZScore[0] deconvWaveformCuts.analyticCorrPeakZScore[1] mapCuts.sphMapPeakZScore[0] mapCuts.sphMapPeakZScore[1] deconvWaveformCuts.fishy[0] deconvWaveformCuts.fishy[1] : deconvWaveformCuts.waveformPeakZScore[0]: +1.000 +0.122 +0.973 -0.667 +0.911 -0.378 +0.949 -0.734 +0.911 -0.647 +0.992 -0.710 +0.992 -0.712 +0.903 -0.695 +0.825 -0.234 : deconvWaveformCuts.waveformPeakZScore[1]: +0.122 +1.000 +0.114 -0.211 -0.007 -0.211 +0.224 -0.060 +0.164 -0.129 +0.112 -0.214 +0.118 -0.208 +0.195 -0.087 +0.147 -0.253 : deconvWaveformCuts.analyticPeakZScore[0]: +0.973 +0.114 +1.000 -0.612 +0.881 -0.313 +0.913 -0.685 +0.877 -0.634 +0.960 -0.664 +0.960 -0.665 +0.905 -0.685 +0.823 -0.236 : deconvWaveformCuts.analyticPeakZScore[1]: -0.667 -0.211 -0.612 +1.000 -0.454 +0.838 -0.721 +0.917 -0.660 +0.866 -0.672 +0.961 -0.671 +0.963 -0.679 +0.847 -0.484 +0.541 : deconvWaveformCuts.linearPolFrac[0]: +0.911 -0.007 +0.881 -0.454 +1.000 -0.127 +0.835 -0.567 +0.834 -0.433 +0.914 -0.496 +0.913 -0.501 +0.790 -0.508 +0.785 +0.002 : deconvWaveformCuts.linearPolFrac[1]: -0.378 -0.211 -0.313 +0.838 -0.127 +1.000 -0.462 +0.780 -0.355 +0.767 -0.386 +0.838 -0.385 +0.836 -0.378 +0.706 -0.154 +0.527 : deconvWaveformCuts.impulsivity[0]: +0.949 +0.224 +0.913 -0.721 +0.835 -0.462 +1.000 -0.721 +0.927 -0.662 +0.949 -0.763 +0.951 -0.762 +0.913 -0.691 +0.821 -0.306 : deconvWaveformCuts.impulsivity[1]: -0.734 -0.060 -0.685 +0.917 -0.567 +0.780 -0.721 +1.000 -0.679 +0.911 -0.741 +0.935 -0.737 +0.939 -0.691 +0.899 -0.514 +0.458 : deconvWaveformCuts.TIMdB[0]: +0.911 +0.164 +0.877 -0.660 +0.834 -0.355 +0.927 -0.679 +1.000 -0.650 +0.910 -0.696 +0.909 -0.697 +0.945 -0.689 +0.934 -0.328 : deconvWaveformCuts.TIMdB[1]: -0.647 -0.129 -0.634 +0.866 -0.433 +0.767 -0.662 +0.911 -0.650 +1.000 -0.651 +0.913 -0.648 +0.912 -0.687 +0.957 -0.535 +0.588 : deconvWaveformCuts.corrPeakZScore[0]: +0.992 +0.112 +0.960 -0.672 +0.914 -0.386 +0.949 -0.741 +0.910 -0.651 +1.000 -0.715 +0.999 -0.718 +0.895 -0.699 +0.818 -0.230 : deconvWaveformCuts.corrPeakZScore[1]: -0.710 -0.214 -0.664 +0.961 -0.496 +0.838 -0.763 +0.935 -0.696 +0.913 -0.715 +1.000 -0.714 +0.999 -0.718 +0.889 -0.529 +0.530 : deconvWaveformCuts.analyticCorrPeakZScore[0]: +0.992 +0.118 +0.960 -0.671 +0.913 -0.385 +0.951 -0.737 +0.909 -0.648 +0.999 -0.714 +1.000 -0.717 +0.894 -0.695 +0.818 -0.230 : deconvWaveformCuts.analyticCorrPeakZScore[1]: -0.712 -0.208 -0.665 +0.963 -0.501 +0.836 -0.762 +0.939 -0.697 +0.912 -0.718 +0.999 -0.717 +1.000 -0.718 +0.887 -0.528 +0.526 : mapCuts.sphMapPeakZScore[0]: +0.903 +0.195 +0.905 -0.679 +0.790 -0.378 +0.913 -0.691 +0.945 -0.687 +0.895 -0.718 +0.894 -0.718 +1.000 -0.710 +0.905 -0.385 : mapCuts.sphMapPeakZScore[1]: -0.695 -0.087 -0.685 +0.847 -0.508 +0.706 -0.691 +0.899 -0.689 +0.957 -0.699 +0.889 -0.695 +0.887 -0.710 +1.000 -0.583 +0.539 : deconvWaveformCuts.fishy[0]: +0.825 +0.147 +0.823 -0.484 +0.785 -0.154 +0.821 -0.514 +0.934 -0.535 +0.818 -0.529 +0.818 -0.528 +0.905 -0.583 +1.000 -0.282 : deconvWaveformCuts.fishy[1]: -0.234 -0.253 -0.236 +0.541 +0.002 +0.527 -0.306 +0.458 -0.328 +0.588 -0.230 +0.530 -0.230 +0.526 -0.385 +0.539 -0.282 +1.000 : --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- DataSetInfo : Correlation matrix (Background): : --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- : deconvWaveformCuts.waveformPeakZScore[0] deconvWaveformCuts.waveformPeakZScore[1] deconvWaveformCuts.analyticPeakZScore[0] deconvWaveformCuts.analyticPeakZScore[1] deconvWaveformCuts.linearPolFrac[0] deconvWaveformCuts.linearPolFrac[1] deconvWaveformCuts.impulsivity[0] deconvWaveformCuts.impulsivity[1] deconvWaveformCuts.TIMdB[0] deconvWaveformCuts.TIMdB[1] deconvWaveformCuts.corrPeakZScore[0] deconvWaveformCuts.corrPeakZScore[1] deconvWaveformCuts.analyticCorrPeakZScore[0] deconvWaveformCuts.analyticCorrPeakZScore[1] mapCuts.sphMapPeakZScore[0] mapCuts.sphMapPeakZScore[1] deconvWaveformCuts.fishy[0] deconvWaveformCuts.fishy[1] : deconvWaveformCuts.waveformPeakZScore[0]: +1.000 -0.005 +0.682 +0.012 +0.017 -0.002 +0.267 +0.004 +0.224 +0.011 +0.605 +0.003 +0.608 +0.002 -0.022 -0.017 +0.373 +0.014 : deconvWaveformCuts.waveformPeakZScore[1]: -0.005 +1.000 -0.009 -0.027 -0.023 -0.016 +0.018 +0.101 -0.009 +0.007 +0.001 +0.005 +0.003 +0.011 +0.025 +0.067 +0.017 -0.233 : deconvWaveformCuts.analyticPeakZScore[0]: +0.682 -0.009 +1.000 +0.044 +0.017 -0.010 +0.203 -0.014 +0.168 -0.003 +0.388 +0.005 +0.400 +0.004 -0.119 -0.055 +0.111 +0.024 : deconvWaveformCuts.analyticPeakZScore[1]: +0.012 -0.027 +0.044 +1.000 +0.031 -0.024 -0.012 +0.177 +0.003 +0.143 +0.003 +0.414 +0.003 +0.426 -0.033 -0.132 -0.066 +0.070 : deconvWaveformCuts.linearPolFrac[0]: +0.017 -0.023 +0.017 +0.031 +1.000 +0.049 -0.004 -0.014 +0.073 +0.017 +0.004 +0.001 -0.003 -0.003 +0.096 -0.122 +0.091 +0.040 : deconvWaveformCuts.linearPolFrac[1]: -0.002 -0.016 -0.010 -0.024 +0.049 +1.000 +0.003 +0.007 +0.008 +0.042 -0.002 -0.048 -0.002 -0.054 +0.050 +0.039 +0.049 +0.031 : deconvWaveformCuts.impulsivity[0]: +0.267 +0.018 +0.203 -0.012 -0.004 +0.003 +1.000 +0.050 +0.239 +0.035 +0.202 +0.005 +0.210 +0.007 +0.036 +0.042 +0.205 -0.032 : deconvWaveformCuts.impulsivity[1]: +0.004 +0.101 -0.014 +0.177 -0.014 +0.007 +0.050 +1.000 +0.034 +0.255 +0.004 +0.199 +0.006 +0.212 +0.021 +0.074 +0.057 -0.067 : deconvWaveformCuts.TIMdB[0]: +0.224 -0.009 +0.168 +0.003 +0.073 +0.008 +0.239 +0.034 +1.000 +0.094 +0.148 +0.006 +0.146 +0.004 +0.001 -0.010 +0.163 +0.016 : deconvWaveformCuts.TIMdB[1]: +0.011 +0.007 -0.003 +0.143 +0.017 +0.042 +0.035 +0.255 +0.094 +1.000 +0.006 +0.145 +0.005 +0.144 +0.004 -0.002 +0.065 +0.024 : deconvWaveformCuts.corrPeakZScore[0]: +0.605 +0.001 +0.388 +0.003 +0.004 -0.002 +0.202 +0.004 +0.148 +0.006 +1.000 +0.001 +0.974 +0.001 +0.001 +0.000 +0.282 -0.001 : deconvWaveformCuts.corrPeakZScore[1]: +0.003 +0.005 +0.005 +0.414 +0.001 -0.048 +0.005 +0.199 +0.006 +0.145 +0.001 +1.000 +0.002 +0.976 +0.002 -0.008 +0.003 -0.002 : deconvWaveformCuts.analyticCorrPeakZScore[0]: +0.608 +0.003 +0.400 +0.003 -0.003 -0.002 +0.210 +0.006 +0.146 +0.005 +0.974 +0.002 +1.000 +0.002 +0.006 +0.005 +0.293 -0.005 : deconvWaveformCuts.analyticCorrPeakZScore[1]: +0.002 +0.011 +0.004 +0.426 -0.003 -0.054 +0.007 +0.212 +0.004 +0.144 +0.001 +0.976 +0.002 +1.000 +0.005 +0.002 +0.004 -0.014 : mapCuts.sphMapPeakZScore[0]: -0.022 +0.025 -0.119 -0.033 +0.096 +0.050 +0.036 +0.021 +0.001 +0.004 +0.001 +0.002 +0.006 +0.005 +1.000 +0.130 +0.284 -0.040 : mapCuts.sphMapPeakZScore[1]: -0.017 +0.067 -0.055 -0.132 -0.122 +0.039 +0.042 +0.074 -0.010 -0.002 +0.000 -0.008 +0.005 +0.002 +0.130 +1.000 +0.101 -0.117 : deconvWaveformCuts.fishy[0]: +0.373 +0.017 +0.111 -0.066 +0.091 +0.049 +0.205 +0.057 +0.163 +0.065 +0.282 +0.003 +0.293 +0.004 +0.284 +0.101 +1.000 -0.036 : deconvWaveformCuts.fishy[1]: +0.014 -0.233 +0.024 +0.070 +0.040 +0.031 -0.032 -0.067 +0.016 +0.024 -0.001 -0.002 -0.005 -0.014 -0.040 -0.117 -0.036 +1.000 : --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- DataSetFactory : [tmvaFiles] : : Factory : [tmvaFiles] : Create Transformation "I" with events from all classes. : : Transformation, Variable selection : : Input : variable 'deconvWaveformCuts.waveformPeakZScore[0]' <---> Output : variable 'deconvWaveformCuts.waveformPeakZScore[0]' : Input : variable 'deconvWaveformCuts.waveformPeakZScore[1]' <---> Output : variable 'deconvWaveformCuts.waveformPeakZScore[1]' : Input : variable 'deconvWaveformCuts.analyticPeakZScore[0]' <---> Output : variable 'deconvWaveformCuts.analyticPeakZScore[0]' : Input : variable 'deconvWaveformCuts.analyticPeakZScore[1]' <---> Output : variable 'deconvWaveformCuts.analyticPeakZScore[1]' : Input : variable 'deconvWaveformCuts.linearPolFrac[0]' <---> Output : variable 'deconvWaveformCuts.linearPolFrac[0]' : Input : variable 'deconvWaveformCuts.linearPolFrac[1]' <---> Output : variable 'deconvWaveformCuts.linearPolFrac[1]' : Input : variable 'deconvWaveformCuts.impulsivity[0]' <---> Output : variable 'deconvWaveformCuts.impulsivity[0]' : Input : variable 'deconvWaveformCuts.impulsivity[1]' <---> Output : variable 'deconvWaveformCuts.impulsivity[1]' : Input : variable 'deconvWaveformCuts.TIMdB[0]' <---> Output : variable 'deconvWaveformCuts.TIMdB[0]' : Input : variable 'deconvWaveformCuts.TIMdB[1]' <---> Output : variable 'deconvWaveformCuts.TIMdB[1]' : Input : variable 'deconvWaveformCuts.corrPeakZScore[0]' <---> Output : variable 'deconvWaveformCuts.corrPeakZScore[0]' : Input : variable 'deconvWaveformCuts.corrPeakZScore[1]' <---> Output : variable 'deconvWaveformCuts.corrPeakZScore[1]' : Input : variable 'deconvWaveformCuts.analyticCorrPeakZScore[0]' <---> Output : variable 'deconvWaveformCuts.analyticCorrPeakZScore[0]' : Input : variable 'deconvWaveformCuts.analyticCorrPeakZScore[1]' <---> Output : variable 'deconvWaveformCuts.analyticCorrPeakZScore[1]' : Input : variable 'mapCuts.sphMapPeakZScore[0]' <---> Output : variable 'mapCuts.sphMapPeakZScore[0]' : Input : variable 'mapCuts.sphMapPeakZScore[1]' <---> Output : variable 'mapCuts.sphMapPeakZScore[1]' : Input : variable 'deconvWaveformCuts.fishy[0]' <---> Output : variable 'deconvWaveformCuts.fishy[0]' : Input : variable 'deconvWaveformCuts.fishy[1]' <---> Output : variable 'deconvWaveformCuts.fishy[1]' TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- : deconvWaveformCuts.waveformPeakZScore[0]: 6.0212 3.2241 [ 2.4671 12.768 ] : deconvWaveformCuts.waveformPeakZScore[1]: 1.4132 0.85764 [ 0.0010894 8.0054 ] : deconvWaveformCuts.analyticPeakZScore[0]: 5.6434 3.2091 [ 1.9727 14.407 ] : deconvWaveformCuts.analyticPeakZScore[1]: 5.1847 2.8575 [ 1.9481 14.155 ] : deconvWaveformCuts.linearPolFrac[0]: 0.39411 0.30546 [ 0.00045970 0.97891 ] : deconvWaveformCuts.linearPolFrac[1]: 0.27948 0.28644 [ 2.2429e-05 0.96600 ] : deconvWaveformCuts.impulsivity[0]: 0.56631 0.22717 [ -0.034713 0.96424 ] : deconvWaveformCuts.impulsivity[1]: 0.53671 0.20893 [ 0.062433 0.96964 ] : deconvWaveformCuts.TIMdB[0]: 20.492 9.0996 [ 7.7121 48.495 ] : deconvWaveformCuts.TIMdB[1]: 18.919 8.2062 [ 7.8450 48.846 ] : deconvWaveformCuts.corrPeakZScore[0]: 9.3258 4.5004 [ 4.1411 18.027 ] : deconvWaveformCuts.corrPeakZScore[1]: 8.6588 4.2591 [ 3.6280 18.588 ] : deconvWaveformCuts.analyticCorrPeakZScore[0]: 6.7178 3.1679 [ 2.9984 12.817 ] : deconvWaveformCuts.analyticCorrPeakZScore[1]: 6.2515 3.0033 [ 2.5974 13.213 ] : mapCuts.sphMapPeakZScore[0]: 8.5678 6.3228 [ 2.9341 26.677 ] : mapCuts.sphMapPeakZScore[1]: 7.3678 5.3130 [ 2.9996 24.553 ] : deconvWaveformCuts.fishy[0]: 30.964 35.074 [ 5.0330 311.07 ] : deconvWaveformCuts.fishy[1]: 0.73854 6.9516 [ -143.05 76.690 ] : ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- : Ranking input variables (method unspecific)... IdTransformation : Ranking result (top variable is best ranked) : --------------------------------------------------------------------- : Rank : Variable : Separation : --------------------------------------------------------------------- : 1 : deconvWaveformCuts.impulsivity[0] : 5.618e-01 : 2 : deconvWaveformCuts.waveformPeakZScore[0] : 5.403e-01 : 3 : deconvWaveformCuts.fishy[0] : 5.357e-01 : 4 : deconvWaveformCuts.analyticCorrPeakZScore[0] : 5.327e-01 : 5 : deconvWaveformCuts.analyticPeakZScore[0] : 5.319e-01 : 6 : deconvWaveformCuts.corrPeakZScore[0] : 5.314e-01 : 7 : mapCuts.sphMapPeakZScore[0] : 5.302e-01 : 8 : deconvWaveformCuts.TIMdB[0] : 5.289e-01 : 9 : deconvWaveformCuts.linearPolFrac[0] : 4.401e-01 : 10 : deconvWaveformCuts.impulsivity[1] : 4.260e-01 : 11 : deconvWaveformCuts.analyticPeakZScore[1] : 4.091e-01 : 12 : deconvWaveformCuts.analyticCorrPeakZScore[1] : 4.042e-01 : 13 : deconvWaveformCuts.corrPeakZScore[1] : 4.008e-01 : 14 : mapCuts.sphMapPeakZScore[1] : 3.818e-01 : 15 : deconvWaveformCuts.TIMdB[1] : 3.816e-01 : 16 : deconvWaveformCuts.linearPolFrac[1] : 3.743e-01 : 17 : deconvWaveformCuts.fishy[1] : 1.554e-01 : 18 : deconvWaveformCuts.waveformPeakZScore[1] : 2.180e-02 : --------------------------------------------------------------------- Factory : Train method: deconvFisher for Classification : deconvFisher : Results for Fisher coefficients: : ------------------------------------------------------------------------------------------- : Variable: Coefficient: : ------------------------------------------------------------------------------------------- : deconvWaveformCuts.waveformPeakZScore[0]: +0.693 : deconvWaveformCuts.waveformPeakZScore[1]: -0.178 : deconvWaveformCuts.analyticPeakZScore[0]: -0.446 : deconvWaveformCuts.analyticPeakZScore[1]: +0.257 : deconvWaveformCuts.linearPolFrac[0]: -4.057 : deconvWaveformCuts.linearPolFrac[1]: -1.982 : deconvWaveformCuts.impulsivity[0]: +4.121 : deconvWaveformCuts.impulsivity[1]: +5.167 : deconvWaveformCuts.TIMdB[0]: +0.153 : deconvWaveformCuts.TIMdB[1]: -0.095 : deconvWaveformCuts.corrPeakZScore[0]: +0.738 : deconvWaveformCuts.corrPeakZScore[1]: +0.208 : deconvWaveformCuts.analyticCorrPeakZScore[0]: -0.509 : deconvWaveformCuts.analyticCorrPeakZScore[1]: +0.454 : mapCuts.sphMapPeakZScore[0]: +0.350 : mapCuts.sphMapPeakZScore[1]: +0.116 : deconvWaveformCuts.fishy[0]: -0.064 : deconvWaveformCuts.fishy[1]: -0.020 : (offset): -17.003 : ------------------------------------------------------------------------------------------- : Elapsed time for training with 866488 events: 4.66 sec deconvFisher : [tmvaFiles] : Evaluation of deconvFisher on training sample (866488 events) : Elapsed time for evaluation of 866488 events: 0.25 sec : Creating xml weight file: tmvaFiles/weights/polarizedReducedFactory_deconvFisher.weights.xml : Creating standalone class: tmvaFiles/weights/polarizedReducedFactory_deconvFisher.class.C Factory : Training finished : : Ranking input variables (method specific)... deconvFisher : Ranking result (top variable is best ranked) : ----------------------------------------------------------------------- : Rank : Variable : Discr. power : ----------------------------------------------------------------------- : 1 : deconvWaveformCuts.impulsivity[0] : 3.361e-01 : 2 : deconvWaveformCuts.analyticCorrPeakZScore[0] : 3.064e-01 : 3 : deconvWaveformCuts.corrPeakZScore[0] : 3.039e-01 : 4 : deconvWaveformCuts.waveformPeakZScore[0] : 3.031e-01 : 5 : deconvWaveformCuts.analyticPeakZScore[0] : 2.763e-01 : 6 : deconvWaveformCuts.TIMdB[0] : 2.712e-01 : 7 : mapCuts.sphMapPeakZScore[0] : 2.707e-01 : 8 : deconvWaveformCuts.impulsivity[1] : 2.378e-01 : 9 : deconvWaveformCuts.linearPolFrac[0] : 2.076e-01 : 10 : deconvWaveformCuts.fishy[0] : 2.068e-01 : 11 : deconvWaveformCuts.analyticCorrPeakZScore[1] : 2.025e-01 : 12 : deconvWaveformCuts.linearPolFrac[1] : 2.008e-01 : 13 : deconvWaveformCuts.corrPeakZScore[1] : 1.986e-01 : 14 : deconvWaveformCuts.analyticPeakZScore[1] : 1.984e-01 : 15 : mapCuts.sphMapPeakZScore[1] : 1.791e-01 : 16 : deconvWaveformCuts.TIMdB[1] : 1.739e-01 : 17 : deconvWaveformCuts.fishy[1] : 2.359e-02 : 18 : deconvWaveformCuts.waveformPeakZScore[1] : 1.949e-03 : ----------------------------------------------------------------------- Factory : === Destroy and recreate all methods via weight files for testing === : Factory : Test all methods Factory : Test method: deconvFisher for Classification performance : deconvFisher : [tmvaFiles] : Evaluation of deconvFisher on testing sample (866488 events) : Elapsed time for evaluation of 866488 events: 0.259 sec Factory : Evaluate all methods Factory : Evaluate classifier: deconvFisher : deconvFisher : [tmvaFiles] : Loop over test events and fill histograms with classifier response... : TFHandler_deconvFisher : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- : deconvWaveformCuts.waveformPeakZScore[0]: 4.3002 1.7974 [ 2.4185 12.912 ] : deconvWaveformCuts.waveformPeakZScore[1]: 1.3704 0.76193 [ 0.00097240 7.3811 ] : deconvWaveformCuts.analyticPeakZScore[0]: 3.9904 1.7688 [ 2.0163 14.351 ] : deconvWaveformCuts.analyticPeakZScore[1]: 3.8988 1.5405 [ 1.8615 13.959 ] : deconvWaveformCuts.linearPolFrac[0]: 0.25419 0.17399 [ 0.00017630 0.97668 ] : deconvWaveformCuts.linearPolFrac[1]: 0.14983 0.15990 [ 8.5749e-05 0.96282 ] : deconvWaveformCuts.impulsivity[0]: 0.44035 0.13700 [ 0.040904 0.96377 ] : deconvWaveformCuts.impulsivity[1]: 0.43541 0.12479 [ -0.023907 0.96733 ] : deconvWaveformCuts.TIMdB[0]: 15.845 5.1343 [ 7.1563 50.337 ] : deconvWaveformCuts.TIMdB[1]: 15.422 4.4949 [ 7.3518 48.116 ] : deconvWaveformCuts.corrPeakZScore[0]: 6.9212 2.5284 [ 4.0827 18.232 ] : deconvWaveformCuts.corrPeakZScore[1]: 6.7387 2.3129 [ 3.6246 18.629 ] : deconvWaveformCuts.analyticCorrPeakZScore[0]: 5.0198 1.7839 [ 2.9467 12.892 ] : deconvWaveformCuts.analyticCorrPeakZScore[1]: 4.8868 1.6369 [ 2.5936 13.212 ] : mapCuts.sphMapPeakZScore[0]: 5.3421 3.4587 [ 2.9223 26.222 ] : mapCuts.sphMapPeakZScore[1]: 5.0774 2.8143 [ 2.9845 24.835 ] : deconvWaveformCuts.fishy[0]: 14.915 18.562 [ 4.9933 340.25 ] : deconvWaveformCuts.fishy[1]: -0.43193 4.3634 [ -66.408 76.040 ] : ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- : : Evaluation results ranked by best signal efficiency and purity (area) : ------------------------------------------------------------------------------------------------------------------- : DataSet MVA : Name: Method: ROC-integ : tmvaFiles deconvFisher : 0.999 : ------------------------------------------------------------------------------------------------------------------- : : Testing efficiency compared to training efficiency (overtraining check) : ------------------------------------------------------------------------------------------------------------------- : DataSet MVA Signal efficiency: from test sample (from training sample) : Name: Method: @B=0.01 @B=0.10 @B=0.30 : ------------------------------------------------------------------------------------------------------------------- : tmvaFiles deconvFisher : 1.000 (1.000) 1.000 (1.000) 1.000 (1.000) : ------------------------------------------------------------------------------------------------------------------- : Dataset:tmvaFiles : Created tree 'TestTree' with 866488 events : Dataset:tmvaFiles : Created tree 'TrainTree' with 866488 events : Factory : Thank you for using TMVA! : For citation information, please visit: http://tmva.sf.net/citeTMVA.html