// Class: ReadBDTG // Automatically generated by MethodBase::MakeClass // /* configuration options ===================================================== #GEN -*-*-*-*-*-*-*-*-*-*-*- general info -*-*-*-*-*-*-*-*-*-*-*- Method : BDT::BDTG TMVA Release : 4.2.1 [262657] ROOT Release : 6.41/01 [403713] Creator : root Date : Tue May 19 20:23:19 2026 Host : Linux d4f37374721b 4.18.0-553.117.1.el8_10.x86_64 #1 SMP Sun Apr 5 23:14:32 EDT 2026 x86_64 GNU/Linux Dir : /github/home/master/notebooks Training events: 3200 Analysis type : [Classification] #OPT -*-*-*-*-*-*-*-*-*-*-*-*- options -*-*-*-*-*-*-*-*-*-*-*-*- # Set by User: V: "False" [Verbose output (short form of "VerbosityLevel" below - overrides the latter one)] H: "True" [Print method-specific help message] NTrees: "100" [Number of trees in the forest] MaxDepth: "2" [Max depth of the decision tree allowed] MinNodeSize: "2.5%" [Minimum percentage of training events required in a leaf node (default: Classification: 5%, Regression: 0.2%)] nCuts: "20" [Number of grid points in variable range used in finding optimal cut in node splitting] BoostType: "Grad" [Boosting type for the trees in the forest (note: AdaCost is still experimental)] UseBaggedBoost: "True" [Use only a random subsample of all events for growing the trees in each boost iteration.] Shrinkage: "1.000000e-01" [Learning rate for BoostType=Grad algorithm] BaggedSampleFraction: "5.000000e-01" [Relative size of bagged event sample to original size of the data sample (used whenever bagging is used (i.e. UseBaggedBoost, Bagging,)] # Default: VerbosityLevel: "Default" [Verbosity level] VarTransform: "None" [List of variable transformations performed before training, e.g., "D_Background,P_Signal,G,N_AllClasses" for: "Decorrelation, PCA-transformation, Gaussianisation, Normalisation, each for the given class of events ('AllClasses' denotes all events of all classes, if no class indication is given, 'All' is assumed)"] CreateMVAPdfs: "False" [Create PDFs for classifier outputs (signal and background)] IgnoreNegWeightsInTraining: "False" [Events with negative weights are ignored in the training (but are included for testing and performance evaluation)] AdaBoostR2Loss: "quadratic" [Type of Loss function in AdaBoostR2] AdaBoostBeta: "5.000000e-01" [Learning rate for AdaBoost algorithm] UseRandomisedTrees: "False" [Determine at each node splitting the cut variable only as the best out of a random subset of variables (like in RandomForests)] UseNvars: "17" [Size of the subset of variables used with RandomisedTree option] UsePoissonNvars: "True" [Interpret "UseNvars" not as fixed number but as mean of a Poisson distribution in each split with RandomisedTree option] UseYesNoLeaf: "True" [Use Sig or Bkg categories, or the purity=S/(S+B) as classification of the leaf node -> Real-AdaBoost] NegWeightTreatment: "pray" [How to treat events with negative weights in the BDT training (particular the boosting) : IgnoreInTraining; Boost With inverse boostweight; Pair events with negative and positive weights in training sample and *annihilate* them (experimental!)] Css: "1.000000e+00" [AdaCost: cost of true signal selected signal] Cts_sb: "1.000000e+00" [AdaCost: cost of true signal selected bkg] Ctb_ss: "1.000000e+00" [AdaCost: cost of true bkg selected signal] Cbb: "1.000000e+00" [AdaCost: cost of true bkg selected bkg ] NodePurityLimit: "5.000000e-01" [In boosting/pruning, nodes with purity > NodePurityLimit are signal; background otherwise.] SeparationType: "giniindex" [Separation criterion for node splitting] RegressionLossFunctionBDTG: "huber" [Loss function for BDTG regression.] HuberQuantile: "7.000000e-01" [In the Huber loss function this is the quantile that separates the core from the tails in the residuals distribution.] DoBoostMonitor: "False" [Create control plot with ROC integral vs tree number] UseFisherCuts: "False" [Use multivariate splits using the Fisher criterion] MinLinCorrForFisher: "8.000000e-01" [The minimum linear correlation between two variables demanded for use in Fisher criterion in node splitting] UseExclusiveVars: "False" [Variables already used in fisher criterion are not anymore analysed individually for node splitting] DoPreselection: "False" [and and apply automatic pre-selection for 100% efficient signal (bkg) cuts prior to training] SigToBkgFraction: "1.000000e+00" [Sig to Bkg ratio used in Training (similar to NodePurityLimit, which cannot be used in real adaboost] PruneMethod: "nopruning" [Note: for BDTs use small trees (e.g.MaxDepth=3) and NoPruning: Pruning: Method used for pruning (removal) of statistically insignificant branches ] PruneStrength: "0.000000e+00" [Pruning strength] PruningValFraction: "5.000000e-01" [Fraction of events to use for optimizing automatic pruning.] SkipNormalization: "False" [Skip normalization at initialization, to keep expectation value of BDT output according to the fraction of events] nEventsMin: "0" [deprecated: Use MinNodeSize (in % of training events) instead] UseBaggedGrad: "False" [deprecated: Use *UseBaggedBoost* instead: Use only a random subsample of all events for growing the trees in each iteration.] GradBaggingFraction: "5.000000e-01" [deprecated: Use *BaggedSampleFraction* instead: Defines the fraction of events to be used in each iteration, e.g. when UseBaggedGrad=kTRUE. ] UseNTrainEvents: "0" [deprecated: Use *BaggedSampleFraction* instead: Number of randomly picked training events used in randomised (and bagged) trees] NNodesMax: "0" [deprecated: Use MaxDepth instead to limit the tree size] ## #VAR -*-*-*-*-*-*-*-*-*-*-*-* variables *-*-*-*-*-*-*-*-*-*-*-*- NVar 300 vars_time0 vars_time0[0] vars_time0 [0] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[1] vars_time0 [1] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[2] vars_time0 [2] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[3] vars_time0 [3] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[4] vars_time0 [4] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[5] vars_time0 [5] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[6] vars_time0 [6] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[7] vars_time0 [7] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[8] vars_time0 [8] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[9] vars_time0 [9] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[10] vars_time0 [10] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[11] vars_time0 [11] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[12] vars_time0 [12] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[13] vars_time0 [13] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[14] vars_time0 [14] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[15] vars_time0 [15] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[16] vars_time0 [16] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[17] vars_time0 [17] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[18] vars_time0 [18] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[19] vars_time0 [19] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[20] vars_time0 [20] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[21] vars_time0 [21] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[22] vars_time0 [22] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[23] vars_time0 [23] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[24] vars_time0 [24] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[25] vars_time0 [25] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[26] vars_time0 [26] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[27] vars_time0 [27] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[28] vars_time0 [28] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time0 vars_time0[29] vars_time0 [29] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[0] vars_time1 [0] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[1] vars_time1 [1] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[2] vars_time1 [2] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[3] vars_time1 [3] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[4] vars_time1 [4] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[5] vars_time1 [5] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[6] vars_time1 [6] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[7] vars_time1 [7] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[8] vars_time1 [8] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[9] vars_time1 [9] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[10] vars_time1 [10] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[11] vars_time1 [11] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[12] vars_time1 [12] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[13] vars_time1 [13] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[14] vars_time1 [14] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[15] vars_time1 [15] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[16] vars_time1 [16] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[17] vars_time1 [17] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[18] vars_time1 [18] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[19] vars_time1 [19] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[20] vars_time1 [20] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[21] vars_time1 [21] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[22] vars_time1 [22] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[23] vars_time1 [23] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[24] vars_time1 [24] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[25] vars_time1 [25] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[26] vars_time1 [26] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[27] vars_time1 [27] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[28] vars_time1 [28] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time1 vars_time1[29] vars_time1 [29] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[0] vars_time2 [0] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[1] vars_time2 [1] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[2] vars_time2 [2] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[3] vars_time2 [3] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[4] vars_time2 [4] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[5] vars_time2 [5] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[6] vars_time2 [6] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[7] vars_time2 [7] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[8] vars_time2 [8] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[9] vars_time2 [9] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[10] vars_time2 [10] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[11] vars_time2 [11] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[12] vars_time2 [12] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[13] vars_time2 [13] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[14] vars_time2 [14] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[15] vars_time2 [15] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[16] vars_time2 [16] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[17] vars_time2 [17] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[18] vars_time2 [18] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[19] vars_time2 [19] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[20] vars_time2 [20] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[21] vars_time2 [21] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[22] vars_time2 [22] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[23] vars_time2 [23] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[24] vars_time2 [24] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[25] vars_time2 [25] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[26] vars_time2 [26] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[27] vars_time2 [27] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[28] vars_time2 [28] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time2 vars_time2[29] vars_time2 [29] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[0] vars_time3 [0] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[1] vars_time3 [1] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[2] vars_time3 [2] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[3] vars_time3 [3] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[4] vars_time3 [4] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[5] vars_time3 [5] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[6] vars_time3 [6] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[7] vars_time3 [7] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[8] vars_time3 [8] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[9] vars_time3 [9] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[10] vars_time3 [10] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[11] vars_time3 [11] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[12] vars_time3 [12] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[13] vars_time3 [13] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[14] vars_time3 [14] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[15] vars_time3 [15] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[16] vars_time3 [16] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[17] vars_time3 [17] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[18] vars_time3 [18] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[19] vars_time3 [19] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[20] vars_time3 [20] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[21] vars_time3 [21] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[22] vars_time3 [22] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[23] vars_time3 [23] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[24] vars_time3 [24] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[25] vars_time3 [25] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[26] vars_time3 [26] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[27] vars_time3 [27] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[28] vars_time3 [28] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time3 vars_time3[29] vars_time3 [29] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[0] vars_time4 [0] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[1] vars_time4 [1] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[2] vars_time4 [2] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[3] vars_time4 [3] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[4] vars_time4 [4] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[5] vars_time4 [5] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[6] vars_time4 [6] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[7] vars_time4 [7] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[8] vars_time4 [8] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[9] vars_time4 [9] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[10] vars_time4 [10] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[11] vars_time4 [11] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[12] vars_time4 [12] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[13] vars_time4 [13] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[14] vars_time4 [14] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[15] vars_time4 [15] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[16] vars_time4 [16] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[17] vars_time4 [17] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[18] vars_time4 [18] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[19] vars_time4 [19] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[20] vars_time4 [20] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[21] vars_time4 [21] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[22] vars_time4 [22] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[23] vars_time4 [23] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time4 vars_time4[24] vars_time4 [24] 'F' 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[6] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[7] vars_time5 [7] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[8] vars_time5 [8] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[9] vars_time5 [9] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[10] vars_time5 [10] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[11] vars_time5 [11] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[12] vars_time5 [12] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[13] vars_time5 [13] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[14] vars_time5 [14] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[15] vars_time5 [15] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[16] vars_time5 [16] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[17] vars_time5 [17] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[18] vars_time5 [18] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[19] vars_time5 [19] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[20] vars_time5 [20] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[21] vars_time5 [21] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[22] vars_time5 [22] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[23] vars_time5 [23] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[24] vars_time5 [24] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[25] vars_time5 [25] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[26] vars_time5 [26] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[27] vars_time5 [27] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[28] vars_time5 [28] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time5 vars_time5[29] vars_time5 [29] 'F' 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vars_time6 [23] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time6 vars_time6[24] vars_time6 [24] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time6 vars_time6[25] vars_time6 [25] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time6 vars_time6[26] vars_time6 [26] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time6 vars_time6[27] vars_time6 [27] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time6 vars_time6[28] vars_time6 [28] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time6 vars_time6[29] vars_time6 [29] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[0] vars_time7 [0] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[1] vars_time7 [1] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[2] vars_time7 [2] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[3] vars_time7 [3] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[4] vars_time7 [4] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[5] vars_time7 [5] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[6] vars_time7 [6] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[7] vars_time7 [7] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[8] vars_time7 [8] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[9] vars_time7 [9] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[10] vars_time7 [10] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[11] vars_time7 [11] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[12] vars_time7 [12] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[13] vars_time7 [13] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[14] vars_time7 [14] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[15] vars_time7 [15] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[16] vars_time7 [16] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[17] vars_time7 [17] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[18] vars_time7 [18] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[19] vars_time7 [19] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[20] vars_time7 [20] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[21] vars_time7 [21] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[22] vars_time7 [22] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[23] vars_time7 [23] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[24] vars_time7 [24] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[25] vars_time7 [25] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[26] vars_time7 [26] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[27] vars_time7 [27] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time7 vars_time7[28] vars_time7 [28] 'F' 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vars_time8 [22] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time8 vars_time8[23] vars_time8 [23] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time8 vars_time8[24] vars_time8 [24] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time8 vars_time8[25] vars_time8 [25] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time8 vars_time8[26] vars_time8 [26] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time8 vars_time8[27] vars_time8 [27] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time8 vars_time8[28] vars_time8 [28] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time8 vars_time8[29] vars_time8 [29] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[0] vars_time9 [0] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[1] vars_time9 [1] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[2] vars_time9 [2] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[3] vars_time9 [3] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[4] vars_time9 [4] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[5] vars_time9 [5] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[6] vars_time9 [6] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[7] vars_time9 [7] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[8] vars_time9 [8] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[9] vars_time9 [9] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[10] vars_time9 [10] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[11] vars_time9 [11] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[12] vars_time9 [12] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[13] vars_time9 [13] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[14] vars_time9 [14] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[15] vars_time9 [15] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[16] vars_time9 [16] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[17] vars_time9 [17] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[18] vars_time9 [18] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[19] vars_time9 [19] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[20] vars_time9 [20] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[21] vars_time9 [21] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[22] vars_time9 [22] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[23] vars_time9 [23] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[24] vars_time9 [24] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[25] vars_time9 [25] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[26] vars_time9 [26] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[27] vars_time9 [27] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[28] vars_time9 [28] 'F' [3.40282346639e+38,-3.40282346639e+38] vars_time9 vars_time9[29] vars_time9 [29] 'F' [3.40282346639e+38,-3.40282346639e+38] NSpec 0 ============================================================================ */ #include #include #include #include #include #include #include #define NN new BDTGNode #ifndef BDTGNode__def #define BDTGNode__def class BDTGNode { public: // constructor of an essentially "empty" node floating in space BDTGNode ( BDTGNode* left,BDTGNode* right, int selector, double cutValue, bool cutType, int nodeType, double purity, double response ) : fLeft ( left ), fRight ( right ), fSelector ( selector ), fCutValue ( cutValue ), fCutType ( cutType ), fNodeType ( nodeType ), fPurity ( purity ), fResponse ( response ){ } virtual ~BDTGNode(); // test event if it descends the tree at this node to the right virtual bool GoesRight( const std::vector& inputValues ) const; BDTGNode* GetRight( void ) {return fRight; }; // test event if it descends the tree at this node to the left virtual bool GoesLeft ( const std::vector& inputValues ) const; BDTGNode* GetLeft( void ) { return fLeft; }; // return S/(S+B) (purity) at this node (from training) double GetPurity( void ) const { return fPurity; } // return the node type int GetNodeType( void ) const { return fNodeType; } double GetResponse(void) const {return fResponse;} private: BDTGNode* fLeft; // pointer to the left daughter node BDTGNode* fRight; // pointer to the right daughter node int fSelector; // index of variable used in node selection (decision tree) double fCutValue; // cut value applied on this node to discriminate bkg against sig bool fCutType; // true: if event variable > cutValue ==> signal , false otherwise int fNodeType; // Type of node: -1 == Bkg-leaf, 1 == Signal-leaf, 0 = internal double fPurity; // Purity of node from training double fResponse; // Regression response value of node }; //_______________________________________________________________________ BDTGNode::~BDTGNode() { if (fLeft != NULL) delete fLeft; if (fRight != NULL) delete fRight; }; //_______________________________________________________________________ bool BDTGNode::GoesRight( const std::vector& inputValues ) const { // test event if it descends the tree at this node to the right bool result; result = (inputValues[fSelector] >= fCutValue ); if (fCutType == true) return result; //the cuts are selecting Signal ; else return !result; } //_______________________________________________________________________ bool BDTGNode::GoesLeft( const std::vector& inputValues ) const { // test event if it descends the tree at this node to the left if (!this->GoesRight(inputValues)) return true; else return false; } #endif #ifndef IClassifierReader__def #define IClassifierReader__def class IClassifierReader { public: // constructor IClassifierReader() : fStatusIsClean( true ) {} virtual ~IClassifierReader() {} // return classifier response virtual double GetMvaValue( const std::vector& inputValues ) const = 0; // returns classifier status bool IsStatusClean() const { return fStatusIsClean; } protected: bool fStatusIsClean; }; #endif class ReadBDTG : public IClassifierReader { public: // constructor ReadBDTG( std::vector& theInputVars ) : IClassifierReader(), fClassName( "ReadBDTG" ), fNvars( 300 ) { // the training input variables const char* inputVars[] = { "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time0", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time1", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time2", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time3", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time4", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time5", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time6", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time7", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time8", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9", "vars_time9" }; // sanity checks if (theInputVars.size() <= 0) { std::cout << "Problem in class \"" << fClassName << "\": empty input vector" << std::endl; fStatusIsClean = false; } if (theInputVars.size() != fNvars) { std::cout << "Problem in class \"" << fClassName << "\": mismatch in number of input values: " << theInputVars.size() << " != " << fNvars << std::endl; fStatusIsClean = false; } // validate input variables for (size_t ivar = 0; ivar < theInputVars.size(); ivar++) { if (theInputVars[ivar] != inputVars[ivar]) { std::cout << "Problem in class \"" << fClassName << "\": mismatch in input variable names" << std::endl << " for variable [" << ivar << "]: " << theInputVars[ivar].c_str() << " != " << inputVars[ivar] << std::endl; fStatusIsClean = false; } } // initialize min and max vectors (for normalisation) fVmin[0] = 0; fVmax[0] = 0; fVmin[1] = 0; fVmax[1] = 0; fVmin[2] = 0; fVmax[2] = 0; fVmin[3] = 0; fVmax[3] = 0; fVmin[4] = 0; fVmax[4] = 0; fVmin[5] = 0; fVmax[5] = 0; fVmin[6] = 0; fVmax[6] = 0; fVmin[7] = 0; fVmax[7] = 0; fVmin[8] = 0; fVmax[8] = 0; fVmin[9] = 0; fVmax[9] = 0; fVmin[10] = 0; fVmax[10] = 0; fVmin[11] = 0; fVmax[11] = 0; fVmin[12] = 0; fVmax[12] = 0; fVmin[13] = 0; fVmax[13] = 0; fVmin[14] = 0; fVmax[14] = 0; fVmin[15] = 0; fVmax[15] = 0; fVmin[16] = 0; fVmax[16] = 0; fVmin[17] = 0; fVmax[17] = 0; fVmin[18] = 0; fVmax[18] = 0; fVmin[19] = 0; fVmax[19] = 0; fVmin[20] = 0; fVmax[20] = 0; fVmin[21] = 0; fVmax[21] = 0; fVmin[22] = 0; fVmax[22] = 0; fVmin[23] = 0; fVmax[23] = 0; fVmin[24] = 0; fVmax[24] = 0; fVmin[25] = 0; fVmax[25] = 0; fVmin[26] = 0; fVmax[26] = 0; fVmin[27] = 0; fVmax[27] = 0; fVmin[28] = 0; fVmax[28] = 0; fVmin[29] = 0; fVmax[29] = 0; fVmin[30] = 0; fVmax[30] = 0; fVmin[31] = 0; fVmax[31] = 0; fVmin[32] = 0; fVmax[32] = 0; fVmin[33] = 0; fVmax[33] = 0; fVmin[34] = 0; fVmax[34] = 0; fVmin[35] = 0; fVmax[35] = 0; fVmin[36] = 0; fVmax[36] = 0; fVmin[37] = 0; fVmax[37] = 0; fVmin[38] = 0; fVmax[38] = 0; fVmin[39] = 0; fVmax[39] = 0; fVmin[40] = 0; fVmax[40] = 0; fVmin[41] = 0; fVmax[41] = 0; fVmin[42] = 0; fVmax[42] = 0; fVmin[43] = 0; fVmax[43] = 0; fVmin[44] = 0; fVmax[44] = 0; fVmin[45] = 0; fVmax[45] = 0; fVmin[46] = 0; fVmax[46] = 0; fVmin[47] = 0; fVmax[47] = 0; fVmin[48] = 0; fVmax[48] = 0; fVmin[49] = 0; fVmax[49] = 0; fVmin[50] = 0; fVmax[50] = 0; fVmin[51] = 0; fVmax[51] = 0; fVmin[52] = 0; fVmax[52] = 0; fVmin[53] = 0; fVmax[53] = 0; fVmin[54] = 0; fVmax[54] = 0; fVmin[55] = 0; fVmax[55] = 0; fVmin[56] = 0; fVmax[56] = 0; fVmin[57] = 0; fVmax[57] = 0; fVmin[58] = 0; fVmax[58] = 0; fVmin[59] = 0; fVmax[59] = 0; fVmin[60] = 0; fVmax[60] = 0; fVmin[61] = 0; fVmax[61] = 0; fVmin[62] = 0; fVmax[62] = 0; fVmin[63] = 0; fVmax[63] = 0; fVmin[64] = 0; fVmax[64] = 0; fVmin[65] = 0; fVmax[65] = 0; fVmin[66] = 0; fVmax[66] = 0; fVmin[67] = 0; fVmax[67] = 0; fVmin[68] = 0; fVmax[68] = 0; fVmin[69] = 0; fVmax[69] = 0; fVmin[70] = 0; fVmax[70] = 0; fVmin[71] = 0; fVmax[71] = 0; fVmin[72] = 0; fVmax[72] = 0; fVmin[73] = 0; fVmax[73] = 0; fVmin[74] = 0; fVmax[74] = 0; fVmin[75] = 0; fVmax[75] = 0; fVmin[76] = 0; fVmax[76] = 0; fVmin[77] = 0; fVmax[77] = 0; fVmin[78] = 0; fVmax[78] = 0; fVmin[79] = 0; fVmax[79] = 0; fVmin[80] = 0; fVmax[80] = 0; fVmin[81] = 0; fVmax[81] = 0; fVmin[82] = 0; fVmax[82] = 0; fVmin[83] = 0; fVmax[83] = 0; fVmin[84] = 0; fVmax[84] = 0; fVmin[85] = 0; fVmax[85] = 0; fVmin[86] = 0; fVmax[86] = 0; fVmin[87] = 0; fVmax[87] = 0; fVmin[88] = 0; fVmax[88] = 0; fVmin[89] = 0; fVmax[89] = 0; fVmin[90] = 0; fVmax[90] = 0; fVmin[91] = 0; fVmax[91] = 0; fVmin[92] = 0; fVmax[92] = 0; fVmin[93] = 0; fVmax[93] = 0; fVmin[94] = 0; fVmax[94] = 0; fVmin[95] = 0; fVmax[95] = 0; fVmin[96] = 0; fVmax[96] = 0; fVmin[97] = 0; fVmax[97] = 0; fVmin[98] = 0; fVmax[98] = 0; fVmin[99] = 0; fVmax[99] = 0; fVmin[100] = 0; fVmax[100] = 0; fVmin[101] = 0; fVmax[101] = 0; fVmin[102] = 0; fVmax[102] = 0; fVmin[103] = 0; fVmax[103] = 0; fVmin[104] = 0; fVmax[104] = 0; fVmin[105] = 0; fVmax[105] = 0; fVmin[106] = 0; fVmax[106] = 0; fVmin[107] = 0; fVmax[107] = 0; fVmin[108] = 0; fVmax[108] = 0; fVmin[109] = 0; fVmax[109] = 0; fVmin[110] = 0; fVmax[110] = 0; fVmin[111] = 0; fVmax[111] = 0; fVmin[112] = 0; fVmax[112] = 0; fVmin[113] = 0; fVmax[113] = 0; fVmin[114] = 0; fVmax[114] = 0; fVmin[115] = 0; fVmax[115] = 0; fVmin[116] = 0; fVmax[116] = 0; fVmin[117] = 0; fVmax[117] = 0; fVmin[118] = 0; fVmax[118] = 0; fVmin[119] = 0; fVmax[119] = 0; fVmin[120] = 0; fVmax[120] = 0; fVmin[121] = 0; fVmax[121] = 0; fVmin[122] = 0; fVmax[122] = 0; fVmin[123] = 0; fVmax[123] = 0; fVmin[124] = 0; fVmax[124] = 0; fVmin[125] = 0; fVmax[125] = 0; fVmin[126] = 0; fVmax[126] = 0; fVmin[127] = 0; fVmax[127] = 0; fVmin[128] = 0; fVmax[128] = 0; fVmin[129] = 0; fVmax[129] = 0; fVmin[130] = 0; fVmax[130] = 0; fVmin[131] = 0; fVmax[131] = 0; fVmin[132] = 0; fVmax[132] = 0; fVmin[133] = 0; fVmax[133] = 0; fVmin[134] = 0; fVmax[134] = 0; fVmin[135] = 0; fVmax[135] = 0; fVmin[136] = 0; fVmax[136] = 0; fVmin[137] = 0; fVmax[137] = 0; fVmin[138] = 0; fVmax[138] = 0; fVmin[139] = 0; fVmax[139] = 0; fVmin[140] = 0; fVmax[140] = 0; fVmin[141] = 0; fVmax[141] = 0; fVmin[142] = 0; fVmax[142] = 0; fVmin[143] = 0; fVmax[143] = 0; fVmin[144] = 0; fVmax[144] = 0; fVmin[145] = 0; fVmax[145] = 0; fVmin[146] = 0; fVmax[146] = 0; fVmin[147] = 0; fVmax[147] = 0; fVmin[148] = 0; fVmax[148] = 0; fVmin[149] = 0; fVmax[149] = 0; fVmin[150] = 0; fVmax[150] = 0; fVmin[151] = 0; fVmax[151] = 0; fVmin[152] = 0; fVmax[152] = 0; fVmin[153] = 0; fVmax[153] = 0; fVmin[154] = 0; fVmax[154] = 0; fVmin[155] = 0; fVmax[155] = 0; fVmin[156] = 0; fVmax[156] = 0; fVmin[157] = 0; fVmax[157] = 0; fVmin[158] = 0; fVmax[158] = 0; fVmin[159] = 0; fVmax[159] = 0; fVmin[160] = 0; fVmax[160] = 0; fVmin[161] = 0; fVmax[161] = 0; fVmin[162] = 0; fVmax[162] = 0; fVmin[163] = 0; fVmax[163] = 0; fVmin[164] = 0; fVmax[164] = 0; fVmin[165] = 0; fVmax[165] = 0; fVmin[166] = 0; fVmax[166] = 0; fVmin[167] = 0; fVmax[167] = 0; fVmin[168] = 0; fVmax[168] = 0; fVmin[169] = 0; fVmax[169] = 0; fVmin[170] = 0; fVmax[170] = 0; fVmin[171] = 0; fVmax[171] = 0; fVmin[172] = 0; fVmax[172] = 0; fVmin[173] = 0; fVmax[173] = 0; fVmin[174] = 0; fVmax[174] = 0; fVmin[175] = 0; fVmax[175] = 0; fVmin[176] = 0; fVmax[176] = 0; fVmin[177] = 0; fVmax[177] = 0; fVmin[178] = 0; fVmax[178] = 0; fVmin[179] = 0; fVmax[179] = 0; fVmin[180] = 0; fVmax[180] = 0; fVmin[181] = 0; fVmax[181] = 0; fVmin[182] = 0; fVmax[182] = 0; fVmin[183] = 0; fVmax[183] = 0; fVmin[184] = 0; fVmax[184] = 0; fVmin[185] = 0; fVmax[185] = 0; fVmin[186] = 0; fVmax[186] = 0; fVmin[187] = 0; fVmax[187] = 0; fVmin[188] = 0; fVmax[188] = 0; fVmin[189] = 0; fVmax[189] = 0; fVmin[190] = 0; fVmax[190] = 0; fVmin[191] = 0; fVmax[191] = 0; fVmin[192] = 0; fVmax[192] = 0; fVmin[193] = 0; fVmax[193] = 0; fVmin[194] = 0; fVmax[194] = 0; fVmin[195] = 0; fVmax[195] = 0; fVmin[196] = 0; fVmax[196] = 0; fVmin[197] = 0; fVmax[197] = 0; fVmin[198] = 0; fVmax[198] = 0; fVmin[199] = 0; fVmax[199] = 0; fVmin[200] = 0; fVmax[200] = 0; fVmin[201] = 0; fVmax[201] = 0; fVmin[202] = 0; fVmax[202] = 0; fVmin[203] = 0; fVmax[203] = 0; fVmin[204] = 0; fVmax[204] = 0; fVmin[205] = 0; fVmax[205] = 0; fVmin[206] = 0; fVmax[206] = 0; fVmin[207] = 0; fVmax[207] = 0; fVmin[208] = 0; fVmax[208] = 0; fVmin[209] = 0; fVmax[209] = 0; fVmin[210] = 0; fVmax[210] = 0; fVmin[211] = 0; fVmax[211] = 0; fVmin[212] = 0; fVmax[212] = 0; fVmin[213] = 0; fVmax[213] = 0; fVmin[214] = 0; fVmax[214] = 0; fVmin[215] = 0; fVmax[215] = 0; fVmin[216] = 0; fVmax[216] = 0; fVmin[217] = 0; fVmax[217] = 0; fVmin[218] = 0; fVmax[218] = 0; fVmin[219] = 0; fVmax[219] = 0; fVmin[220] = 0; fVmax[220] = 0; fVmin[221] = 0; fVmax[221] = 0; fVmin[222] = 0; fVmax[222] = 0; fVmin[223] = 0; fVmax[223] = 0; fVmin[224] = 0; fVmax[224] = 0; fVmin[225] = 0; fVmax[225] = 0; fVmin[226] = 0; fVmax[226] = 0; fVmin[227] = 0; fVmax[227] = 0; fVmin[228] = 0; fVmax[228] = 0; fVmin[229] = 0; fVmax[229] = 0; fVmin[230] = 0; fVmax[230] = 0; fVmin[231] = 0; fVmax[231] = 0; fVmin[232] = 0; fVmax[232] = 0; fVmin[233] = 0; fVmax[233] = 0; fVmin[234] = 0; fVmax[234] = 0; fVmin[235] = 0; fVmax[235] = 0; fVmin[236] = 0; fVmax[236] = 0; fVmin[237] = 0; fVmax[237] = 0; fVmin[238] = 0; fVmax[238] = 0; fVmin[239] = 0; fVmax[239] = 0; fVmin[240] = 0; fVmax[240] = 0; fVmin[241] = 0; fVmax[241] = 0; fVmin[242] = 0; fVmax[242] = 0; fVmin[243] = 0; fVmax[243] = 0; fVmin[244] = 0; fVmax[244] = 0; fVmin[245] = 0; fVmax[245] = 0; fVmin[246] = 0; fVmax[246] = 0; fVmin[247] = 0; fVmax[247] = 0; fVmin[248] = 0; fVmax[248] = 0; fVmin[249] = 0; fVmax[249] = 0; fVmin[250] = 0; fVmax[250] = 0; fVmin[251] = 0; fVmax[251] = 0; fVmin[252] = 0; fVmax[252] = 0; fVmin[253] = 0; fVmax[253] = 0; fVmin[254] = 0; fVmax[254] = 0; fVmin[255] = 0; fVmax[255] = 0; fVmin[256] = 0; fVmax[256] = 0; fVmin[257] = 0; fVmax[257] = 0; fVmin[258] = 0; fVmax[258] = 0; fVmin[259] = 0; fVmax[259] = 0; fVmin[260] = 0; fVmax[260] = 0; fVmin[261] = 0; fVmax[261] = 0; fVmin[262] = 0; fVmax[262] = 0; fVmin[263] = 0; fVmax[263] = 0; fVmin[264] = 0; fVmax[264] = 0; fVmin[265] = 0; fVmax[265] = 0; fVmin[266] = 0; fVmax[266] = 0; fVmin[267] = 0; fVmax[267] = 0; fVmin[268] = 0; fVmax[268] = 0; fVmin[269] = 0; fVmax[269] = 0; fVmin[270] = 0; fVmax[270] = 0; fVmin[271] = 0; fVmax[271] = 0; fVmin[272] = 0; fVmax[272] = 0; fVmin[273] = 0; fVmax[273] = 0; fVmin[274] = 0; fVmax[274] = 0; fVmin[275] = 0; fVmax[275] = 0; fVmin[276] = 0; fVmax[276] = 0; fVmin[277] = 0; fVmax[277] = 0; fVmin[278] = 0; fVmax[278] = 0; fVmin[279] = 0; fVmax[279] = 0; fVmin[280] = 0; fVmax[280] = 0; fVmin[281] = 0; fVmax[281] = 0; fVmin[282] = 0; fVmax[282] = 0; fVmin[283] = 0; fVmax[283] = 0; fVmin[284] = 0; fVmax[284] = 0; fVmin[285] = 0; fVmax[285] = 0; fVmin[286] = 0; fVmax[286] = 0; fVmin[287] = 0; fVmax[287] = 0; fVmin[288] = 0; fVmax[288] = 0; fVmin[289] = 0; fVmax[289] = 0; fVmin[290] = 0; fVmax[290] = 0; fVmin[291] = 0; fVmax[291] = 0; fVmin[292] = 0; fVmax[292] = 0; fVmin[293] = 0; fVmax[293] = 0; fVmin[294] = 0; fVmax[294] = 0; fVmin[295] = 0; fVmax[295] = 0; fVmin[296] = 0; fVmax[296] = 0; fVmin[297] = 0; fVmax[297] = 0; fVmin[298] = 0; fVmax[298] = 0; fVmin[299] = 0; fVmax[299] = 0; // initialize input variable types fType[0] = 'F'; fType[1] = 'F'; fType[2] = 'F'; fType[3] = 'F'; fType[4] = 'F'; fType[5] = 'F'; fType[6] = 'F'; fType[7] = 'F'; fType[8] = 'F'; fType[9] = 'F'; fType[10] = 'F'; fType[11] = 'F'; fType[12] = 'F'; fType[13] = 'F'; fType[14] = 'F'; fType[15] = 'F'; fType[16] = 'F'; fType[17] = 'F'; fType[18] = 'F'; fType[19] = 'F'; fType[20] = 'F'; fType[21] = 'F'; fType[22] = 'F'; fType[23] = 'F'; fType[24] = 'F'; fType[25] = 'F'; fType[26] = 'F'; fType[27] = 'F'; fType[28] = 'F'; fType[29] = 'F'; fType[30] = 'F'; fType[31] = 'F'; fType[32] = 'F'; fType[33] = 'F'; fType[34] = 'F'; fType[35] = 'F'; fType[36] = 'F'; fType[37] = 'F'; fType[38] = 'F'; fType[39] = 'F'; fType[40] = 'F'; fType[41] = 'F'; fType[42] = 'F'; fType[43] = 'F'; fType[44] = 'F'; fType[45] = 'F'; fType[46] = 'F'; fType[47] = 'F'; fType[48] = 'F'; fType[49] = 'F'; fType[50] = 'F'; fType[51] = 'F'; fType[52] = 'F'; fType[53] = 'F'; fType[54] = 'F'; fType[55] = 'F'; fType[56] = 'F'; fType[57] = 'F'; fType[58] = 'F'; fType[59] = 'F'; fType[60] = 'F'; fType[61] = 'F'; fType[62] = 'F'; fType[63] = 'F'; fType[64] = 'F'; fType[65] = 'F'; fType[66] = 'F'; fType[67] = 'F'; fType[68] = 'F'; fType[69] = 'F'; fType[70] = 'F'; fType[71] = 'F'; fType[72] = 'F'; fType[73] = 'F'; fType[74] = 'F'; fType[75] = 'F'; fType[76] = 'F'; fType[77] = 'F'; fType[78] = 'F'; fType[79] = 'F'; fType[80] = 'F'; fType[81] = 'F'; fType[82] = 'F'; fType[83] = 'F'; fType[84] = 'F'; fType[85] = 'F'; fType[86] = 'F'; fType[87] = 'F'; fType[88] = 'F'; fType[89] = 'F'; fType[90] = 'F'; fType[91] = 'F'; fType[92] = 'F'; fType[93] = 'F'; fType[94] = 'F'; fType[95] = 'F'; fType[96] = 'F'; fType[97] = 'F'; fType[98] = 'F'; fType[99] = 'F'; fType[100] = 'F'; fType[101] = 'F'; fType[102] = 'F'; fType[103] = 'F'; fType[104] = 'F'; fType[105] = 'F'; fType[106] = 'F'; fType[107] = 'F'; fType[108] = 'F'; fType[109] = 'F'; fType[110] = 'F'; fType[111] = 'F'; fType[112] = 'F'; fType[113] = 'F'; fType[114] = 'F'; fType[115] = 'F'; fType[116] = 'F'; fType[117] = 'F'; fType[118] = 'F'; fType[119] = 'F'; fType[120] = 'F'; fType[121] = 'F'; fType[122] = 'F'; fType[123] = 'F'; fType[124] = 'F'; fType[125] = 'F'; fType[126] = 'F'; fType[127] = 'F'; fType[128] = 'F'; fType[129] = 'F'; fType[130] = 'F'; fType[131] = 'F'; fType[132] = 'F'; fType[133] = 'F'; fType[134] = 'F'; fType[135] = 'F'; fType[136] = 'F'; fType[137] = 'F'; fType[138] = 'F'; fType[139] = 'F'; fType[140] = 'F'; fType[141] = 'F'; fType[142] = 'F'; fType[143] = 'F'; fType[144] = 'F'; fType[145] = 'F'; fType[146] = 'F'; fType[147] = 'F'; fType[148] = 'F'; fType[149] = 'F'; fType[150] = 'F'; fType[151] = 'F'; fType[152] = 'F'; fType[153] = 'F'; fType[154] = 'F'; fType[155] = 'F'; fType[156] = 'F'; fType[157] = 'F'; fType[158] = 'F'; fType[159] = 'F'; fType[160] = 'F'; fType[161] = 'F'; fType[162] = 'F'; fType[163] = 'F'; fType[164] = 'F'; fType[165] = 'F'; fType[166] = 'F'; fType[167] = 'F'; fType[168] = 'F'; fType[169] = 'F'; fType[170] = 'F'; fType[171] = 'F'; fType[172] = 'F'; fType[173] = 'F'; fType[174] = 'F'; fType[175] = 'F'; fType[176] = 'F'; fType[177] = 'F'; fType[178] = 'F'; fType[179] = 'F'; fType[180] = 'F'; fType[181] = 'F'; fType[182] = 'F'; fType[183] = 'F'; fType[184] = 'F'; fType[185] = 'F'; fType[186] = 'F'; fType[187] = 'F'; fType[188] = 'F'; fType[189] = 'F'; fType[190] = 'F'; fType[191] = 'F'; fType[192] = 'F'; fType[193] = 'F'; fType[194] = 'F'; fType[195] = 'F'; fType[196] = 'F'; fType[197] = 'F'; fType[198] = 'F'; fType[199] = 'F'; fType[200] = 'F'; fType[201] = 'F'; fType[202] = 'F'; fType[203] = 'F'; fType[204] = 'F'; fType[205] = 'F'; fType[206] = 'F'; fType[207] = 'F'; fType[208] = 'F'; fType[209] = 'F'; fType[210] = 'F'; fType[211] = 'F'; fType[212] = 'F'; fType[213] = 'F'; fType[214] = 'F'; fType[215] = 'F'; fType[216] = 'F'; fType[217] = 'F'; fType[218] = 'F'; fType[219] = 'F'; fType[220] = 'F'; fType[221] = 'F'; fType[222] = 'F'; fType[223] = 'F'; fType[224] = 'F'; fType[225] = 'F'; fType[226] = 'F'; fType[227] = 'F'; fType[228] = 'F'; fType[229] = 'F'; fType[230] = 'F'; fType[231] = 'F'; fType[232] = 'F'; fType[233] = 'F'; fType[234] = 'F'; fType[235] = 'F'; fType[236] = 'F'; fType[237] = 'F'; fType[238] = 'F'; fType[239] = 'F'; fType[240] = 'F'; fType[241] = 'F'; fType[242] = 'F'; fType[243] = 'F'; fType[244] = 'F'; fType[245] = 'F'; fType[246] = 'F'; fType[247] = 'F'; fType[248] = 'F'; fType[249] = 'F'; fType[250] = 'F'; fType[251] = 'F'; fType[252] = 'F'; fType[253] = 'F'; fType[254] = 'F'; fType[255] = 'F'; fType[256] = 'F'; fType[257] = 'F'; fType[258] = 'F'; fType[259] = 'F'; fType[260] = 'F'; fType[261] = 'F'; fType[262] = 'F'; fType[263] = 'F'; fType[264] = 'F'; fType[265] = 'F'; fType[266] = 'F'; fType[267] = 'F'; fType[268] = 'F'; fType[269] = 'F'; fType[270] = 'F'; fType[271] = 'F'; fType[272] = 'F'; fType[273] = 'F'; fType[274] = 'F'; fType[275] = 'F'; fType[276] = 'F'; fType[277] = 'F'; fType[278] = 'F'; fType[279] = 'F'; fType[280] = 'F'; fType[281] = 'F'; fType[282] = 'F'; fType[283] = 'F'; fType[284] = 'F'; fType[285] = 'F'; fType[286] = 'F'; fType[287] = 'F'; fType[288] = 'F'; fType[289] = 'F'; fType[290] = 'F'; fType[291] = 'F'; fType[292] = 'F'; fType[293] = 'F'; fType[294] = 'F'; fType[295] = 'F'; fType[296] = 'F'; fType[297] = 'F'; fType[298] = 'F'; fType[299] = 'F'; // initialize constants Initialize(); } // destructor virtual ~ReadBDTG() { Clear(); // method-specific } // the classifier response // "inputValues" is a vector of input values in the same order as the // variables given to the constructor double GetMvaValue( const std::vector& inputValues ) const override; private: // method-specific destructor void Clear(); // common member variables const char* fClassName; const size_t fNvars; size_t GetNvar() const { return fNvars; } char GetType( int ivar ) const { return fType[ivar]; } // normalisation of input variables double fVmin[300]; double fVmax[300]; double NormVariable( double x, double xmin, double xmax ) const { // normalise to output range: [-1, 1] return 2*(x - xmin)/(xmax - xmin) - 1.0; } // type of input variable: 'F' or 'I' char fType[300]; // initialize internal variables void Initialize(); double GetMvaValue__( const std::vector& inputValues ) const; // private members (method specific) std::vector fForest; // i.e. root nodes of decision trees std::vector fBoostWeights; // the weights applied in the individual boosts }; double ReadBDTG::GetMvaValue__( const std::vector& inputValues ) const { double myMVA = 0; for (unsigned int itree=0; itreeGetNodeType() == 0) { //intermediate node if (current->GoesRight(inputValues)) current=(BDTGNode*)current->GetRight(); else current=(BDTGNode*)current->GetLeft(); } myMVA += current->GetResponse(); } return 2.0/(1.0+exp(-2.0*myMVA))-1.0; } void ReadBDTG::Initialize() { double inf = std::numeric_limits::infinity(); double nan = std::numeric_limits::quiet_NaN(); // itree = 0 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.242718,-0.0514563) , NN( 0, 0, -1, 0, 1, -99, 0.440594,-0.0118812) , 159, 24.4219, 1, 0, 0.411848,-0.0881523) , NN( NN( 0, 0, -1, 0, 1, -99, 0.424837,-0.0150327) , NN( 0, 0, -1, 0, 1, -99, 0.616774,0.0233548) , 150, 10.0846, 1, 0, 0.585129,0.0851293) , 219, 36.4721, 1, 0, 0.510079,0.0100794) ); // itree = 1 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.469809,-0.00619741) , NN( 0, 0, -1, 0, 1, -99, 0.272727,-0.0453374) , 210, 30.7094, 1, 0, 0.437731,-0.0628042) , NN( NN( 0, 0, -1, 0, 1, -99, 0.851064,0.0699101) , NN( 0, 0, -1, 0, 1, -99, 0.542675,0.00832326) , 6, 13.121, 1, 0, 0.560096,0.0589823) , 279, 38.2099, 1, 0, 0.499696,-0.00113264) ); // itree = 2 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.297735,-0.040896) , NN( 0, 0, -1, 0, 1, -99, 0.46472,-0.00729245) , 276, 30.6069, 1, 0, 0.393056,-0.108473) , NN( NN( 0, 0, -1, 0, 1, -99, 0.444444,-0.0112515) , NN( 0, 0, -1, 0, 1, -99, 0.601942,0.0201664) , 247, 32.4246, 1, 0, 0.536199,0.0352359) , 278, 35.0479, 1, 0, 0.471945,-0.0292717) ); // itree = 3 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.409621,-0.0176437) , NN( 0, 0, -1, 0, 1, -99, 0.579151,0.0161474) , 274, 35.6881, 1, 0, 0.456085,-0.041856) , NN( NN( 0, 0, -1, 0, 1, -99, 0.430556,-0.0120152) , NN( 0, 0, -1, 0, 1, -99, 0.628151,0.0252955) , 219, 29.7964, 1, 0, 0.582258,0.0830217) , 246, 36.122, 1, 0, 0.50607,0.0076163) ); // itree = 4 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.590308,0.0191095) , NN( 0, 0, -1, 0, 1, -99, 0.433824,-0.0128161) , 5, 19.7583, 1, 0, 0.460836,-0.0364616) , NN( NN( 0, 0, -1, 0, 1, -99, 0.45679,-0.00799038) , NN( 0, 0, -1, 0, 1, -99, 0.77381,0.0536128) , 246, 27.6356, 1, 0, 0.670683,0.167553) , 278, 48.2545, 1, 0, 0.494246,-0.00398092) ); // itree = 5 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.401493,-0.0188383) , NN( 0, 0, -1, 0, 1, -99, 0.536634,0.00750678) , 218, 38.7992, 1, 0, 0.459574,-0.0374722) , NN( NN( 0, 0, -1, 0, 1, -99, 0.554913,0.0112409) , NN( 0, 0, -1, 0, 1, -99, 0.778947,0.0558359) , 215, 40.6441, 1, 0, 0.603175,0.104003) , 275, 37.5906, 1, 0, 0.498762,0.00113568) ); // itree = 6 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.396682,-0.0176514) , NN( 0, 0, -1, 0, 1, -99, 0.634921,0.0273857) , 218, 48.1174, 1, 0, 0.434727,-0.0521016) , NN( NN( 0, 0, -1, 0, 1, -99, 0.54721,0.00762516) , NN( 0, 0, -1, 0, 1, -99, 0.68693,0.035559) , 159, 40.1861, 1, 0, 0.605031,0.0956327) , 278, 36.9472, 1, 0, 0.520202,0.0220453) ); // itree = 7 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.396226,-0.0204886) , NN( 0, 0, -1, 0, 1, -99, 0.670996,0.0335677) , 3, 15.929, 1, 0, 0.619718,0.116717) , NN( NN( 0, 0, -1, 0, 1, -99, 0.426456,-0.0142248) , NN( 0, 0, -1, 0, 1, -99, 0.604444,0.0183547) , 219, 49.1988, 1, 0, 0.458805,-0.0413646) , 6, 21.5075, 1, 0, 0.48883,-0.011867) ); // itree = 8 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.424672,-0.0134209) , NN( 0, 0, -1, 0, 1, -99, 0.547237,0.00887081) , 246, 36.4711, 1, 0, 0.471225,-0.024686) , NN( NN( 0, 0, -1, 0, 1, -99, 0.914894,0.0795237) , NN( 0, 0, -1, 0, 1, -99, 0.590164,0.0129087) , 128, 32.0045, 1, 0, 0.731481,0.208284) , 219, 55.6995, 1, 0, 0.488959,-0.00881176) ); // itree = 9 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.501149,0.00295295) , NN( 0, 0, -1, 0, 1, -99, 0.367925,-0.0220973) , 6, 31.9452, 1, 0, 0.43539,-0.0467625) , NN( NN( 0, 0, -1, 0, 1, -99, 0.632653,0.0236822) , NN( 0, 0, -1, 0, 1, -99, 0.381679,-0.0254684) , 5, 40.2913, 1, 0, 0.586926,0.0731909) , 278, 38.6099, 1, 0, 0.504436,0.00789309) ); // itree = 10 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.443907,-0.010779) , NN( 0, 0, -1, 0, 1, -99, 0.643411,0.0271301) , 276, 47.4937, 1, 0, 0.466036,-0.032645) , NN( NN( 0, 0, -1, 0, 1, -99, 0.735099,0.0473178) , NN( 0, 0, -1, 0, 1, -99, 0.523077,0.00581494) , 181, 17.691, 1, 0, 0.600973,0.104657) , 158, 43.5185, 1, 0, 0.501271,0.0032071) ); // itree = 11 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.518072,0.00368661) , NN( 0, 0, -1, 0, 1, -99, 0.716763,0.044044) , 157, 41.3238, 1, 0, 0.576531,0.0772169) , NN( NN( 0, 0, -1, 0, 1, -99, 0.303371,-0.0379751) , NN( 0, 0, -1, 0, 1, -99, 0.475222,-0.00461472) , 279, 27.8026, 1, 0, 0.443523,-0.0534909) , 8, 32.8102, 1, 0, 0.493883,-0.00400207) ); // itree = 12 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.585774,0.016515) , NN( 0, 0, -1, 0, 1, -99, 0.416539,-0.0167115) , 34, 22.1376, 1, 0, 0.461883,-0.0387523) , NN( NN( 0, 0, -1, 0, 1, -99, 0.328947,-0.0303806) , NN( 0, 0, -1, 0, 1, -99, 0.623639,0.0243033) , 219, 23.884, 1, 0, 0.59249,0.0918927) , 188, 37.1884, 1, 0, 0.520174,0.0195554) ); // itree = 13 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.284211,-0.0418888) , NN( 0, 0, -1, 0, 1, -99, 0.481884,-0.0022878) , 182, 21.2412, 1, 0, 0.401288,-0.0915507) , NN( NN( 0, 0, -1, 0, 1, -99, 0.479947,-0.00350644) , NN( 0, 0, -1, 0, 1, -99, 0.612245,0.0207214) , 276, 38.1496, 1, 0, 0.529016,0.0272) , 244, 22.2394, 1, 0, 0.493051,-0.00623672) ); // itree = 14 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.769231,0.0474008) , NN( 0, 0, -1, 0, 1, -99, 0.417383,-0.014835) , 6, 13.8187, 1, 0, 0.434031,-0.0590148) , NN( NN( 0, 0, -1, 0, 1, -99, 0.531414,0.00413171) , NN( 0, 0, -1, 0, 1, -99, 0.754386,0.0493879) , 2, 32.1757, 1, 0, 0.582661,0.0721115) , 218, 42.1726, 1, 0, 0.480251,-0.0182382) ); // itree = 15 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.575342,0.014884) , NN( 0, 0, -1, 0, 1, -99, 0.409034,-0.0154889) , 5, 23.7978, 1, 0, 0.453627,-0.0363798) , NN( NN( 0, 0, -1, 0, 1, -99, 0.444444,-0.00944401) , NN( 0, 0, -1, 0, 1, -99, 0.698225,0.0340125) , 278, 30.071, 1, 0, 0.62931,0.10948) , 219, 44.2437, 1, 0, 0.506117,0.00719969) ); // itree = 16 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.393225,-0.0208343) , NN( 0, 0, -1, 0, 1, -99, 0.559829,0.0112905) , 150, 28.7404, 1, 0, 0.435926,-0.0623468) , NN( NN( 0, 0, -1, 0, 1, -99, 0.60452,0.0205041) , NN( 0, 0, -1, 0, 1, -99, 0.351351,-0.0262665) , 8, 46.5485, 1, 0, 0.560748,0.0613276) , 189, 40.3284, 1, 0, 0.48746,-0.0112864) ); // itree = 17 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.242188,-0.0463393) , NN( 0, 0, -1, 0, 1, -99, 0.461538,-0.00617287) , 158, 27.9777, 1, 0, 0.402923,-0.08346) , NN( NN( 0, 0, -1, 0, 1, -99, 0.41704,-0.0165197) , NN( 0, 0, -1, 0, 1, -99, 0.573789,0.0151362) , 243, 17.1183, 1, 0, 0.542882,0.0437725) , 189, 30.821, 1, 0, 0.501242,0.00591886) ); // itree = 18 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.4914,-0.000751995) , NN( 0, 0, -1, 0, 1, -99, 0.662125,0.031098) , 279, 38.5876, 1, 0, 0.572351,0.0708518) , NN( NN( 0, 0, -1, 0, 1, -99, 0.361635,-0.0268372) , NN( 0, 0, -1, 0, 1, -99, 0.506276,0.00202019) , 186, 29.6429, 1, 0, 0.448492,-0.0470321) , 9, 36.8888, 1, 0, 0.509554,0.0110839) ); // itree = 19 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.255814,-0.0420721) , NN( 0, 0, -1, 0, 1, -99, 0.491749,-0.00288682) , 219, 24.1012, 1, 0, 0.462428,-0.0382856) , NN( NN( 0, 0, -1, 0, 1, -99, 0.485611,-0.001922) , NN( 0, 0, -1, 0, 1, -99, 0.657534,0.0313451) , 245, 30.6094, 1, 0, 0.573684,0.0744954) , 216, 37.0171, 1, 0, 0.501866,0.00169275) ); // itree = 20 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.463094,-0.00766634) , NN( 0, 0, -1, 0, 1, -99, 0.177215,-0.0597894) , 6, 48.8142, 1, 0, 0.441948,-0.0567715) , NN( NN( 0, 0, -1, 0, 1, -99, 0.645161,0.0289789) , NN( 0, 0, -1, 0, 1, -99, 0.466667,-0.0042995) , 271, 23.6545, 1, 0, 0.557377,0.0621393) , 277, 40.6059, 1, 0, 0.481138,-0.0163992) ); // itree = 21 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.387844,-0.0207201) , NN( 0, 0, -1, 0, 1, -99, 0.661017,0.0250186) , 278, 48.8391, 1, 0, 0.427689,-0.069523) , NN( NN( 0, 0, -1, 0, 1, -99, 0.48552,-0.00235656) , NN( 0, 0, -1, 0, 1, -99, 0.669456,0.0340851) , 215, 37.6091, 1, 0, 0.538741,0.040158) , 126, 32.0296, 1, 0, 0.483792,-0.0141123) ); // itree = 22 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.436759,-0.0118825) , NN( 0, 0, -1, 0, 1, -99, 0.638298,0.0281521) , 248, 48.0773, 1, 0, 0.468333,-0.0276451) , NN( NN( 0, 0, -1, 0, 1, -99, 0.819444,0.0637847) , NN( 0, 0, -1, 0, 1, -99, 0.574007,0.0147599) , 184, 19.3054, 1, 0, 0.624642,0.122432) , 214, 37.8668, 1, 0, 0.503551,0.00616825) ); // itree = 23 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.509554,0.000162179) , NN( 0, 0, -1, 0, 1, -99, 0.684588,0.0353902) , 248, 33.8249, 1, 0, 0.62156,0.111688) , NN( NN( 0, 0, -1, 0, 1, -99, 0.52669,0.00640084) , NN( 0, 0, -1, 0, 1, -99, 0.410385,-0.0165179) , 97, 33.8488, 1, 0, 0.466782,-0.026566) , 8, 29.0818, 1, 0, 0.509091,0.0112264) ); // itree = 24 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.494706,-0.000966294) , NN( 0, 0, -1, 0, 1, -99, 0.344697,-0.0299118) , 94, 37.3887, 1, 0, 0.464313,-0.0335589) , NN( NN( 0, 0, -1, 0, 1, -99, 0.323529,-0.0286635) , NN( 0, 0, -1, 0, 1, -99, 0.646154,0.028142) , 279, 26.7513, 1, 0, 0.590331,0.0900741) , 249, 46.3878, 1, 0, 0.493514,-0.00491043) ); // itree = 25 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.468271,-0.00311988) , NN( 0, 0, -1, 0, 1, -99, 0.265734,-0.0434271) , 38, 43.1807, 1, 0, 0.42,-0.0624841) , NN( NN( 0, 0, -1, 0, 1, -99, 0.619744,0.0226797) , NN( 0, 0, -1, 0, 1, -99, 0.487805,-0.00359988) , 39, 39.1451, 1, 0, 0.56012,0.0530392) , 158, 31.8108, 1, 0, 0.507509,0.00966375) ); // itree = 26 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.378378,-0.0235138) , NN( 0, 0, -1, 0, 1, -99, 0.508294,0.00223069) , 124, 25.8532, 1, 0, 0.458884,-0.0370445) , NN( NN( 0, 0, -1, 0, 1, -99, 0.47561,-0.0052063) , NN( 0, 0, -1, 0, 1, -99, 0.722222,0.0433614) , 157, 33.0383, 1, 0, 0.639344,0.132536) , 273, 39.4548, 1, 0, 0.486301,-0.0112801) ); // itree = 27 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.292553,-0.0394592) , NN( 0, 0, -1, 0, 1, -99, 0.467192,-0.00683579) , 126, 27.6817, 1, 0, 0.40949,-0.0863398) , NN( NN( 0, 0, -1, 0, 1, -99, 0.491315,-0.0011415) , NN( 0, 0, -1, 0, 1, -99, 0.652174,0.0310666) , 1, 30.1253, 1, 0, 0.529745,0.0321713) , 277, 29.8212, 1, 0, 0.487715,-0.00924937) ); // itree = 28 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.572581,0.0089125) , NN( 0, 0, -1, 0, 1, -99, 0.786517,0.0505992) , 242, 21.873, 1, 0, 0.698676,0.163245) , NN( NN( 0, 0, -1, 0, 1, -99, 0.162791,-0.0677511) , NN( 0, 0, -1, 0, 1, -99, 0.474684,-0.00321364) , 217, 13.1427, 1, 0, 0.464422,-0.0262378) , 6, 21.5075, 1, 0, 0.50839,0.00932696) ); // itree = 29 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.651376,0.0262893) , NN( 0, 0, -1, 0, 1, -99, 0.377778,-0.0298399) , 128, 49.8175, 1, 0, 0.61828,0.0954747) , NN( NN( 0, 0, -1, 0, 1, -99, 0.35034,-0.0249857) , NN( 0, 0, -1, 0, 1, -99, 0.504625,0.00143684) , 279, 29.3425, 1, 0, 0.468824,-0.0230328) , 8, 27.3018, 1, 0, 0.502746,0.00386458) ); // itree = 30 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.31694,-0.0287986) , NN( 0, 0, -1, 0, 1, -99, 0.582524,0.0179561) , 218, 44.5215, 1, 0, 0.375267,-0.0903068) , NN( NN( 0, 0, -1, 0, 1, -99, 0.42268,-0.0159805) , NN( 0, 0, -1, 0, 1, -99, 0.595304,0.0155923) , 247, 31.3178, 1, 0, 0.535072,0.0222663) , 219, 30.9687, 1, 0, 0.487666,-0.0111283) ); // itree = 31 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.344569,-0.0298012) , NN( 0, 0, -1, 0, 1, -99, 0.489437,-0.000506954) , 187, 28.6051, 1, 0, 0.443114,-0.048208) , NN( NN( 0, 0, -1, 0, 1, -99, 0.656593,0.0322778) , NN( 0, 0, -1, 0, 1, -99, 0.508353,0.00248436) , 152, 23.3701, 1, 0, 0.577267,0.0796516) , 216, 33.5768, 1, 0, 0.508035,0.0136672) ); // itree = 32 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.573913,0.0167348) , NN( 0, 0, -1, 0, 1, -99, 0.375258,-0.0236594) , 157, 23.4976, 1, 0, 0.413333,-0.0776539) , NN( NN( 0, 0, -1, 0, 1, -99, 0.492308,-0.00155205) , NN( 0, 0, -1, 0, 1, -99, 0.634006,0.0252724) , 187, 38.9867, 1, 0, 0.541625,0.0380457) , 216, 29.4495, 1, 0, 0.493425,-0.00542316) ); // itree = 33 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.386282,-0.0181921) , NN( 0, 0, -1, 0, 1, -99, 0.527778,0.00444168) , 158, 33.6364, 1, 0, 0.471056,-0.0225939) , NN( NN( 0, 0, -1, 0, 1, -99, 0.537879,0.00470012) , NN( 0, 0, -1, 0, 1, -99, 0.7875,0.0539471) , 127, 36.3163, 1, 0, 0.632075,0.113472) , 273, 39.9788, 1, 0, 0.492472,-0.00449724) ); // itree = 34 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.368644,-0.0224879) , NN( 0, 0, -1, 0, 1, -99, 0.517711,0.00342435) , 246, 30.1836, 1, 0, 0.45937,-0.0326359) , NN( NN( 0, 0, -1, 0, 1, -99, 0.647799,0.0284951) , NN( 0, 0, -1, 0, 1, -99, 0.368421,-0.0244519) , 9, 48.9436, 1, 0, 0.605333,0.0993242) , 248, 44.3287, 1, 0, 0.493991,-0.00133608) ); // itree = 35 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.464401,-0.00571796) , NN( 0, 0, -1, 0, 1, -99, 0.624339,0.0242045) , 159, 50.0297, 1, 0, 0.485614,-0.00857833) , NN( NN( 0, 0, -1, 0, 1, -99, 0.61,0.0204047) , NN( 0, 0, -1, 0, 1, -99, 0.906977,0.0773056) , 215, 43.3889, 1, 0, 0.662551,0.148113) , 275, 42.0424, 1, 0, 0.511391,0.0142491) ); // itree = 36 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.474916,-0.00273085) , NN( 0, 0, -1, 0, 1, -99, 0.60198,0.0184771) , 277, 39.8338, 1, 0, 0.520685,0.0238005) , NN( NN( 0, 0, -1, 0, 1, -99, 0.458015,-0.0117971) , NN( 0, 0, -1, 0, 1, -99, 0.190476,-0.0649915) , 210, 28.993, 1, 0, 0.393064,-0.120651) , 63, 40.825, 1, 0, 0.506667,0.00793374) ); // itree = 37 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.105263,-0.0751772) , NN( 0, 0, -1, 0, 1, -99, 0.477273,-0.000556276) , 242, 29.1642, 1, 0, 0.267327,-0.208309) , NN( NN( 0, 0, -1, 0, 1, -99, 0.335196,-0.0267775) , NN( 0, 0, -1, 0, 1, -99, 0.529688,0.00413896) , 278, 24.8224, 1, 0, 0.505826,0.00157208) , 248, 18.3719, 1, 0, 0.490385,-0.0120164) ); // itree = 38 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.150943,-0.067478) , NN( 0, 0, -1, 0, 1, -99, 0.465228,-0.00460263) , 125, 16.7484, 1, 0, 0.429787,-0.0562851) , NN( NN( 0, 0, -1, 0, 1, -99, 0.507712,0.00137703) , NN( 0, 0, -1, 0, 1, -99, 0.647059,0.0281026) , 180, 25.5223, 1, 0, 0.551542,0.047439) , 276, 27.5404, 1, 0, 0.515888,0.017065) ); // itree = 39 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.432927,-0.0108998) , NN( 0, 0, -1, 0, 1, -99, 0.211009,-0.0512315) , 9, 39.5903, 1, 0, 0.344322,-0.131068) , NN( NN( 0, 0, -1, 0, 1, -99, 0.517771,0.00288174) , NN( 0, 0, -1, 0, 1, -99, 0.320988,-0.0356148) , 69, 53.7474, 1, 0, 0.505686,0.00257737) , 217, 24.2234, 1, 0, 0.478015,-0.0203405) ); // itree = 40 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.776596,0.0554425) , NN( 0, 0, -1, 0, 1, -99, 0.44898,-0.0049743) , 5, 33.6482, 1, 0, 0.664336,0.167295) , NN( NN( 0, 0, -1, 0, 1, -99, 0.458525,-0.00789115) , NN( 0, 0, -1, 0, 1, -99, 0.70229,0.0340623) , 273, 43.0097, 1, 0, 0.480809,-0.019722) , 36, 15.7711, 1, 0, 0.497462,-0.00275278) ); // itree = 41 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.546939,0.00877102) , NN( 0, 0, -1, 0, 1, -99, 0.379859,-0.0217417) , 67, 27.1334, 1, 0, 0.430333,-0.0606843) , NN( NN( 0, 0, -1, 0, 1, -99, 0.530769,0.00488868) , NN( 0, 0, -1, 0, 1, -99, 0.716418,0.0419586) , 245, 42.1988, 1, 0, 0.5625,0.0542959) , 159, 37.4114, 1, 0, 0.495298,-0.00416738) ); // itree = 42 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.432882,-0.0101742) , NN( 0, 0, -1, 0, 1, -99, 0.596413,0.019697) , 157, 44.946, 1, 0, 0.463682,-0.0219421) , NN( NN( 0, 0, -1, 0, 1, -99, 0.466667,-0.0081726) , NN( 0, 0, -1, 0, 1, -99, 0.66092,0.0281325) , 93, 21.1503, 1, 0, 0.611111,0.0908925) , 277, 41.3203, 1, 0, 0.505448,0.0100231) ); // itree = 43 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.533333,0.00896047) , NN( 0, 0, -1, 0, 1, -99, 0.353276,-0.0228759) , 9, 37.8359, 1, 0, 0.438438,-0.0375236) , NN( NN( 0, 0, -1, 0, 1, -99, 0.507299,0.00121091) , NN( 0, 0, -1, 0, 1, -99, 0.638122,0.0266272) , 96, 34.4337, 1, 0, 0.559341,0.0547324) , 218, 33.2674, 1, 0, 0.508249,0.015746) ); // itree = 44 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.457831,-0.0042827) , NN( 0, 0, -1, 0, 1, -99, 0.197802,-0.0559804) , 155, 31.5482, 1, 0, 0.321839,-0.153073) , NN( NN( 0, 0, -1, 0, 1, -99, 0.418367,-0.0168076) , NN( 0, 0, -1, 0, 1, -99, 0.551837,0.0104056) , 247, 21.9492, 1, 0, 0.533427,0.0321485) , 244, 15.3535, 1, 0, 0.510345,0.0119426) ); // itree = 45 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.311828,-0.0293484) , NN( 0, 0, -1, 0, 1, -99, 0.573106,0.0124509) , 278, 20.715, 1, 0, 0.549515,0.0419073) , NN( NN( 0, 0, -1, 0, 1, -99, 0.230769,-0.0478599) , NN( 0, 0, -1, 0, 1, -99, 0.456212,-0.0060875) , 37, 21.811, 1, 0, 0.420962,-0.0608059) , 8, 40.2671, 1, 0, 0.503102,0.00482351) ); // itree = 46 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.12963,-0.070381) , NN( 0, 0, -1, 0, 1, -99, 0.395349,-0.0171583) , 273, 24.6497, 1, 0, 0.292857,-0.183368) , NN( NN( 0, 0, -1, 0, 1, -99, 0.452991,-0.00734432) , NN( 0, 0, -1, 0, 1, -99, 0.572816,0.0125618) , 273, 28.2698, 1, 0, 0.509091,0.00952616) , 157, 17.7411, 1, 0, 0.491071,-0.00654832) ); // itree = 47 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.548387,0.0112947) , NN( 0, 0, -1, 0, 1, -99, 0.824324,0.0648241) , 216, 44.6146, 1, 0, 0.591195,0.0947248) , NN( NN( 0, 0, -1, 0, 1, -99, 0.275862,-0.0434927) , NN( 0, 0, -1, 0, 1, -99, 0.502793,-0.000821985) , 275, 14.0307, 1, 0, 0.485788,-0.0192215) , 215, 24.4602, 1, 0, 0.516484,0.0139606) ); // itree = 48 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.462617,-0.00695914) , NN( 0, 0, -1, 0, 1, -99, 0.640187,0.0237316) , 277, 47.9309, 1, 0, 0.487984,-0.0124784) , NN( 0, 0, -1, 0, 1, -99, 0.741379,0.0472681) , 247, 56.334, 1, 0, 0.497429,-0.00350893) ); // itree = 49 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.601351,0.0201767) , NN( 0, 0, -1, 0, 1, -99, 0.43949,-0.0143314) , 272, 31.8926, 1, 0, 0.559068,0.054101) , NN( NN( 0, 0, -1, 0, 1, -99, 0.35109,-0.0258866) , NN( 0, 0, -1, 0, 1, -99, 0.51746,0.0020076) , 216, 29.543, 1, 0, 0.451582,-0.0434588) , 270, 16.4553, 1, 0, 0.490876,-0.0077937) ); // itree = 50 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.384393,-0.0218353) , NN( 0, 0, -1, 0, 1, -99, 0.518519,0.00576366) , 245, 37.8972, 1, 0, 0.419251,-0.0706514) , NN( NN( 0, 0, -1, 0, 1, -99, 0.220339,-0.0578123) , NN( 0, 0, -1, 0, 1, -99, 0.574961,0.0140638) , 127, 16.4567, 1, 0, 0.545326,0.039069) , 188, 38.659, 1, 0, 0.473492,-0.0234468) ); // itree = 51 fBoostWeights.push_back(1); fForest.push_back( NN( NN( 0, 0, -1, 0, 1, -99, 0.275362,-0.0460331) , NN( NN( 0, 0, -1, 0, 1, -99, 0.344828,-0.0344455) , NN( 0, 0, -1, 0, 1, -99, 0.529815,0.00583538) , 212, 7.04108, 1, 0, 0.519405,0.0171884) , 153, 7.07216, 1, 0, 0.508978,0.00713242) ); // itree = 52 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.495396,0.00123639) , NN( 0, 0, -1, 0, 1, -99, 0.354167,-0.0264559) , 69, 38.2701, 1, 0, 0.42913,-0.0564393) , NN( NN( 0, 0, -1, 0, 1, -99, 0.606061,0.0173025) , NN( 0, 0, -1, 0, 1, -99, 0.373832,-0.029967) , 0, 30.2114, 1, 0, 0.56239,0.0403017) , 276, 37.4649, 1, 0, 0.476759,-0.0218629) ); // itree = 53 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.33,-0.0347171) , NN( 0, 0, -1, 0, 1, -99, 0.525703,0.00596464) , 151, 5.98117, 1, 0, 0.513149,0.0161154) , NN( 0, 0, -1, 0, 1, -99, 0.148936,-0.0670163) , 128, 57.509, 1, 0, 0.502491,0.00615188) ); // itree = 54 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.385396,-0.0183567) , NN( 0, 0, -1, 0, 1, -99, 0.508117,0.00372704) , 182, 22.7991, 1, 0, 0.453562,-0.029239) , NN( NN( 0, 0, -1, 0, 1, -99, 0.785714,0.0479618) , NN( 0, 0, -1, 0, 1, -99, 0.557971,0.00745297) , 5, 20.075, 1, 0, 0.596386,0.0686976) , 218, 42.1726, 1, 0, 0.497822,0.00111102) ); // itree = 55 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.527406,0.00416053) , NN( 0, 0, -1, 0, 1, -99, 0.811765,0.0516513) , 278, 51.8415, 1, 0, 0.554084,0.0409979) , NN( NN( 0, 0, -1, 0, 1, -99, 0.497382,-0.000376951) , NN( 0, 0, -1, 0, 1, -99, 0.308682,-0.0310639) , 8, 37.6868, 1, 0, 0.412698,-0.0678406) , 9, 38.9526, 1, 0, 0.492808,-0.00617224) ); // itree = 56 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.4672,-0.00519675) , NN( 0, 0, -1, 0, 1, -99, 0.654028,0.0272397) , 247, 46.638, 1, 0, 0.494182,-0.00239835) , NN( 0, 0, -1, 0, 1, -99, 0.757576,0.0539679) , 126, 53.9362, 1, 0, 0.505566,0.00873136) ); // itree = 57 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.265152,-0.0446342) , NN( 0, 0, -1, 0, 1, -99, 0.488722,0.000275156) , 154, 28.5291, 1, 0, 0.377358,-0.106284) , NN( NN( 0, 0, -1, 0, 1, -99, 0.387387,-0.0195979) , NN( 0, 0, -1, 0, 1, -99, 0.564648,0.0123022) , 249, 25.7891, 1, 0, 0.537396,0.0353248) , 244, 17.5491, 1, 0, 0.51258,0.0133668) ); // itree = 58 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.142857,-0.0748251) , NN( 0, 0, -1, 0, 1, -99, 0.431138,-0.0120628) , 154, 17.4231, 1, 0, 0.365741,-0.127037) , NN( NN( 0, 0, -1, 0, 1, -99, 0.46868,-0.00505417) , NN( 0, 0, -1, 0, 1, -99, 0.60251,0.0207181) , 182, 29.2403, 1, 0, 0.515306,0.0186481) , 32, 13.2059, 1, 0, 0.494962,-0.00116797) ); // itree = 59 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.473118,-0.00236259) , NN( 0, 0, -1, 0, 1, -99, 0.677824,0.0353746) , 245, 29.9289, 1, 0, 0.588235,0.0894688) , NN( NN( 0, 0, -1, 0, 1, -99, 0.33617,-0.0314465) , NN( 0, 0, -1, 0, 1, -99, 0.505566,0.000891672) , 187, 23.7437, 1, 0, 0.475248,-0.0233535) , 180, 12.9142, 1, 0, 0.502877,0.00423538) ); // itree = 60 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.511628,0.00325905) , NN( 0, 0, -1, 0, 1, -99, 0.372603,-0.0207216) , 38, 37.7022, 1, 0, 0.447799,-0.0367964) , NN( NN( 0, 0, -1, 0, 1, -99, 0.394737,-0.0140444) , NN( 0, 0, -1, 0, 1, -99, 0.62234,0.0197998) , 278, 30.0614, 1, 0, 0.556818,0.0478116) , 159, 37.4114, 1, 0, 0.502205,0.00542764) ); // itree = 61 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.350365,-0.0287309) , NN( 0, 0, -1, 0, 1, -99, 0.506173,-0.000346746) , 124, 24.985, 1, 0, 0.45,-0.0506251) , NN( NN( 0, 0, -1, 0, 1, -99, 0.517018,0.00263089) , NN( 0, 0, -1, 0, 1, -99, 0.686916,0.034836) , 249, 46.9104, 1, 0, 0.56077,0.0519241) , 127, 33.2578, 1, 0, 0.507857,0.0029377) ); // itree = 62 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.426752,-0.00443738) , NN( 0, 0, -1, 0, 1, -99, 0.219298,-0.0455306) , 5, 31.6729, 1, 0, 0.339483,-0.102724) , NN( NN( 0, 0, -1, 0, 1, -99, 0.522401,0.00241694) , NN( 0, 0, -1, 0, 1, -99, 0.674074,0.0365162) , 66, 46.9146, 1, 0, 0.537936,0.0281677) , 219, 27.4836, 1, 0, 0.504091,0.00584447) ); // itree = 63 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.486874,-0.00305385) , NN( 0, 0, -1, 0, 1, -99, 0.260274,-0.0412462) , 9, 44.6951, 1, 0, 0.428319,-0.0623958) , NN( NN( 0, 0, -1, 0, 1, -99, 0.15,-0.0633003) , NN( 0, 0, -1, 0, 1, -99, 0.555098,0.0100907) , 249, 16.7491, 1, 0, 0.53907,0.0342279) , 186, 28.5144, 1, 0, 0.499365,-0.00041193) ); // itree = 64 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.29771,-0.0390241) , NN( 0, 0, -1, 0, 1, -99, 0.493708,-0.00136534) , 155, 15.8778, 1, 0, 0.476383,-0.0220233) , NN( NN( 0, 0, -1, 0, 1, -99, 0.6875,0.0206867) , NN( 0, 0, -1, 0, 1, -99, 0.877551,0.0651485) , 61, 22.1043, 1, 0, 0.783505,0.201829) , 247, 52.8955, 1, 0, 0.49525,-0.00827174) ); // itree = 65 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.183099,-0.0674175) , NN( 0, 0, -1, 0, 1, -99, 0.408163,-0.0111051) , 95, 21.2802, 1, 0, 0.348315,-0.12357) , NN( NN( 0, 0, -1, 0, 1, -99, 0.533163,0.00618861) , NN( 0, 0, -1, 0, 1, -99, 0.380952,-0.0256496) , 91, 36.6888, 1, 0, 0.516251,0.012578) , 189, 24.9711, 1, 0, 0.48805,-0.0102845) ); // itree = 66 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.334197,-0.0292657) , NN( 0, 0, -1, 0, 1, -99, 0.504951,-0.00171049) , 188, 35.436, 1, 0, 0.421519,-0.0720136) , NN( NN( 0, 0, -1, 0, 1, -99, 0.613583,0.021648) , NN( 0, 0, -1, 0, 1, -99, 0.46747,-0.00656755) , 67, 35.0079, 1, 0, 0.541568,0.0367028) , 0, 20.732, 1, 0, 0.483456,-0.0159234) ); // itree = 67 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.31405,-0.0360522) , NN( 0, 0, -1, 0, 1, -99, 0.50173,0.00156586) , 215, 16.9238, 1, 0, 0.483947,-0.00969012) , NN( NN( 0, 0, -1, 0, 1, -99, 0.521472,0.0023321) , NN( 0, 0, -1, 0, 1, -99, 0.724719,0.0437249) , 242, 22.9213, 1, 0, 0.627566,0.113236) , 214, 37.8668, 1, 0, 0.514215,0.016217) ); // itree = 68 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.785714,0.0593421) , NN( 0, 0, -1, 0, 1, -99, 0.477612,-0.00402745) , 96, 31.785, 1, 0, 0.635036,0.135532) , NN( NN( 0, 0, -1, 0, 1, -99, 0.428438,-0.0120594) , NN( 0, 0, -1, 0, 1, -99, 0.568965,0.0100635) , 246, 40.9556, 1, 0, 0.46295,-0.0313794) , 69, 21.8593, 1, 0, 0.478121,-0.0166646) ); // itree = 69 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.690476,0.0384497) , NN( 0, 0, -1, 0, 1, -99, 0.368852,-0.0202156) , 9, 20.3274, 1, 0, 0.39434,-0.0736032) , NN( NN( 0, 0, -1, 0, 1, -99, 0.619128,0.0202114) , NN( 0, 0, -1, 0, 1, -99, 0.481876,-0.00351082) , 67, 36.8146, 1, 0, 0.558685,0.0465189) , 218, 31.5301, 1, 0, 0.504075,0.00660371) ); // itree = 70 fBoostWeights.push_back(1); fForest.push_back( NN( NN( 0, 0, -1, 0, 1, -99, 0.195652,-0.0543855) , NN( NN( 0, 0, -1, 0, 1, -99, 0.571906,0.0150014) , NN( 0, 0, -1, 0, 1, -99, 0.473204,-0.00505819) , 61, 20.001, 1, 0, 0.51322,0.0145355) , 212, 3.82079, 1, 0, 0.503616,0.00625655) ); // itree = 71 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.465863,-0.00560278) , NN( 0, 0, -1, 0, 1, -99, 0.599251,0.0200841) , 129, 48.2524, 1, 0, 0.489418,-0.0051041) , NN( NN( 0, 0, -1, 0, 1, -99, 0.956522,0.0869475) , NN( 0, 0, -1, 0, 1, -99, 0.557692,0.00535924) , 274, 27.2385, 1, 0, 0.744898,0.204887) , 275, 48.2042, 1, 0, 0.504969,0.00767795) ); // itree = 72 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.34715,-0.0296622) , NN( 0, 0, -1, 0, 1, -99, 0.500416,0.00029311) , 153, 14.7607, 1, 0, 0.479197,-0.018304) , NN( NN( 0, 0, -1, 0, 1, -99, 0.509202,0.00768859) , NN( 0, 0, -1, 0, 1, -99, 0.811111,0.059915) , 216, 37.6736, 1, 0, 0.616601,0.124715) , 241, 33.7974, 1, 0, 0.500304,0.00366558) ); // itree = 73 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.496063,0.00254139) , NN( 0, 0, -1, 0, 1, -99, 0.665236,0.0335585) , 32, 27.5325, 1, 0, 0.560261,0.0670211) , NN( NN( 0, 0, -1, 0, 1, -99, 0.353319,-0.0246471) , NN( 0, 0, -1, 0, 1, -99, 0.551471,0.00413207) , 218, 36.535, 1, 0, 0.459941,-0.0431761) , 2, 20.0024, 1, 0, 0.497846,-0.00153854) ); // itree = 74 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.373464,-0.0231319) , NN( 0, 0, -1, 0, 1, -99, 0.616667,0.0314985) , 211, 34.8545, 1, 0, 0.404711,-0.0768623) , NN( NN( 0, 0, -1, 0, 1, -99, 0.633721,0.0249233) , NN( 0, 0, -1, 0, 1, -99, 0.484887,-0.0024747) , 69, 29.838, 1, 0, 0.529877,0.0274119) , 273, 20.8132, 1, 0, 0.493458,-0.00292831) ); // itree = 75 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.298429,-0.0327363) , NN( 0, 0, -1, 0, 1, -99, 0.492147,-0.000625319) , 189, 24.8894, 1, 0, 0.464473,-0.0243684) , NN( NN( 0, 0, -1, 0, 1, -99, 0.442308,-0.0205484) , NN( 0, 0, -1, 0, 1, -99, 0.680628,0.0340798) , 62, 17.5905, 1, 0, 0.62963,0.105494) , 275, 41.2445, 1, 0, 0.489873,-0.00439595) ); // itree = 76 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.494021,0.000283434) , NN( 0, 0, -1, 0, 1, -99, 0.65,0.0329988) , 213, 43.8935, 1, 0, 0.504868,0.0121183) , NN( NN( 0, 0, -1, 0, 1, -99, 0.893617,0.0751951) , NN( 0, 0, -1, 0, 1, -99, 0.645833,0.0184963) , 91, 20.8441, 1, 0, 0.768421,0.218986) , 248, 53.6675, 1, 0, 0.5212,0.0249379) ); // itree = 77 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.423773,-0.0118236) , NN( 0, 0, -1, 0, 1, -99, 0.551302,0.00748155) , 188, 37.7254, 1, 0, 0.48213,-0.014262) , NN( NN( 0, 0, -1, 0, 1, -99, 0.692737,0.0369896) , NN( 0, 0, -1, 0, 1, -99, 0.444444,-0.0147962) , 245, 39.8345, 1, 0, 0.635193,0.117224) , 180, 32.3422, 1, 0, 0.503614,0.0041936) ); // itree = 78 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.386189,-0.0198464) , NN( 0, 0, -1, 0, 1, -99, 0.530713,0.00669516) , 157, 33.3507, 1, 0, 0.4599,-0.0293429) , NN( NN( 0, 0, -1, 0, 1, -99, 0.435583,-0.0150424) , NN( 0, 0, -1, 0, 1, -99, 0.628389,0.0215791) , 249, 28.3444, 1, 0, 0.588608,0.0652403) , 247, 35.7031, 1, 0, 0.523929,0.0177104) ); // itree = 79 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.610577,0.0218506) , NN( 0, 0, -1, 0, 1, -99, 0.476852,-0.00784316) , 90, 26.0196, 1, 0, 0.564873,0.0547601) , NN( NN( 0, 0, -1, 0, 1, -99, 0.430572,-0.0123583) , NN( 0, 0, -1, 0, 1, -99, 0.670455,0.0304397) , 248, 50.5088, 1, 0, 0.45291,-0.0395626) , 7, 31.0542, 1, 0, 0.497781,-0.00176176) ); // itree = 80 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.517483,0.00893998) , NN( 0, 0, -1, 0, 1, -99, 0.285714,-0.0401691) , 35, 27.6384, 1, 0, 0.385542,-0.0901306) , NN( NN( 0, 0, -1, 0, 1, -99, 0.53967,0.00626546) , NN( 0, 0, -1, 0, 1, -99, 0.863636,0.0633528) , 218, 59.3709, 1, 0, 0.550494,0.0385314) , 279, 28.6909, 1, 0, 0.517283,0.0126273) ); // itree = 81 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.318182,-0.0378629) , NN( 0, 0, -1, 0, 1, -99, 0.475118,-0.00408213) , 242, 14.0889, 1, 0, 0.448039,-0.0463558) , NN( NN( 0, 0, -1, 0, 1, -99, 0.43609,-0.00646574) , NN( 0, 0, -1, 0, 1, -99, 0.643678,0.0218334) , 278, 35.3562, 1, 0, 0.553746,0.0443553) , 126, 35.9092, 1, 0, 0.48776,-0.0122698) ); // itree = 82 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.454733,-0.00850525) , NN( 0, 0, -1, 0, 1, -99, 0.177419,-0.0584041) , 6, 46.5416, 1, 0, 0.423358,-0.0654842) , NN( NN( 0, 0, -1, 0, 1, -99, 0.562136,0.0114155) , NN( 0, 0, -1, 0, 1, -99, 0.272727,-0.0462782) , 212, 42.4731, 1, 0, 0.547465,0.0398425) , 213, 21.3885, 1, 0, 0.505818,0.00449713) ); // itree = 83 fBoostWeights.push_back(1); fForest.push_back( NN( NN( 0, 0, -1, 0, 1, -99, 0.728814,0.0462376) , NN( NN( 0, 0, -1, 0, 1, -99, 0.4375,-0.011399) , NN( 0, 0, -1, 0, 1, -99, 0.545018,0.00707479) , 214, 26.4937, 1, 0, 0.49701,-0.00568163) , 98, 14.4192, 1, 0, 0.505754,0.00271492) ); // itree = 84 fBoostWeights.push_back(1); fForest.push_back( NN( NN( 0, 0, -1, 0, 1, -99, 0.133333,-0.0655934) , NN( NN( 0, 0, -1, 0, 1, -99, 0.448441,-0.00960603) , NN( 0, 0, -1, 0, 1, -99, 0.560664,0.00992179) , 127, 33.7027, 1, 0, 0.502783,-0.000671912) , 189, 13.5791, 1, 0, 0.49278,-0.00907753) ); // itree = 85 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.43734,-0.013083) , NN( 0, 0, -1, 0, 1, -99, 0.522472,0.00564106) , 123, 26.8539, 1, 0, 0.477912,-0.0195751) , NN( 0, 0, -1, 0, 1, -99, 0.782609,0.0430267) , 218, 56.219, 1, 0, 0.491363,-0.00984026) ); // itree = 86 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.463415,-0.000892711) , NN( 0, 0, -1, 0, 1, -99, 0.138889,-0.0654796) , 150, 20.4978, 1, 0, 0.256637,-0.193315) , NN( NN( 0, 0, -1, 0, 1, -99, 0.483392,-0.00379199) , NN( 0, 0, -1, 0, 1, -99, 0.684932,0.0417186) , 64, 47.6537, 1, 0, 0.49328,-0.00716185) , 159, 19.9644, 1, 0, 0.476577,-0.0203007) ); // itree = 87 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.194805,-0.0587632) , NN( 0, 0, -1, 0, 1, -99, 0.45341,-0.0075839) , 2, 6.60439, 1, 0, 0.435599,-0.0522779) , NN( NN( 0, 0, -1, 0, 1, -99, 0.755814,0.0488823) , NN( 0, 0, -1, 0, 1, -99, 0.535109,0.00216799) , 96, 21.8387, 1, 0, 0.573146,0.0475332) , 279, 44.8039, 1, 0, 0.478046,-0.0214766) ); // itree = 88 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.483636,-0.00142952) , NN( 0, 0, -1, 0, 1, -99, 0.293023,-0.0366547) , 39, 38.8399, 1, 0, 0.4,-0.0790633) , NN( NN( 0, 0, -1, 0, 1, -99, 0.291667,-0.0249838) , NN( 0, 0, -1, 0, 1, -99, 0.556352,0.0107838) , 219, 24.274, 1, 0, 0.522321,0.0296095) , 127, 27.6885, 1, 0, 0.485093,-0.00346485) ); // itree = 89 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.376689,-0.020311) , NN( 0, 0, -1, 0, 1, -99, 0.544379,0.00494083) , 188, 37.5917, 1, 0, 0.454049,-0.0404735) , NN( NN( 0, 0, -1, 0, 1, -99, 0.729167,0.0458854) , NN( 0, 0, -1, 0, 1, -99, 0.526178,0.0061883) , 152, 15.6308, 1, 0, 0.566946,0.0657527) , 274, 34.6661, 1, 0, 0.488269,-0.00827555) ); // itree = 90 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.379808,-0.022076) , NN( 0, 0, -1, 0, 1, -99, 0.619048,0.0168149) , 249, 45.843, 1, 0, 0.435424,-0.0612107) , NN( NN( 0, 0, -1, 0, 1, -99, 0.285714,-0.030768) , NN( 0, 0, -1, 0, 1, -99, 0.561297,0.0112416) , 278, 19.4206, 1, 0, 0.539683,0.0371101) , 274, 24.0072, 1, 0, 0.50465,0.00407234) ); // itree = 91 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.780488,0.0605704) , NN( 0, 0, -1, 0, 1, -99, 0.634146,0.0276757) , 245, 29.8278, 1, 0, 0.707317,0.205926) , NN( NN( 0, 0, -1, 0, 1, -99, 0.461676,-0.00739327) , NN( 0, 0, -1, 0, 1, -99, 0.563805,0.0124908) , 215, 37.825, 1, 0, 0.490019,-0.0089907) , 3, 8.79716, 1, 0, 0.500917,0.00178799) ); // itree = 92 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.338384,-0.0309898) , NN( 0, 0, -1, 0, 1, -99, 0.589041,0.0172725) , 152, 32.5568, 1, 0, 0.405904,-0.0836345) , NN( NN( 0, 0, -1, 0, 1, -99, 0.486146,-0.00088833) , NN( 0, 0, -1, 0, 1, -99, 0.620482,0.0187527) , 276, 36.1183, 1, 0, 0.537926,0.031193) , 124, 17.9604, 1, 0, 0.515035,0.0112837) ); // itree = 93 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.464258,-0.00530104) , NN( 0, 0, -1, 0, 1, -99, 0.650406,0.0307224) , 31, 36.9127, 1, 0, 0.480659,-0.00965507) , NN( NN( 0, 0, -1, 0, 1, -99, 0.737589,0.0425099) , NN( 0, 0, -1, 0, 1, -99, 0.390244,-0.019622) , 212, 34.5357, 1, 0, 0.659341,0.133691) , 159, 51.0487, 1, 0, 0.501267,0.00687784) ); // itree = 94 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.42439,-0.00722741) , NN( 0, 0, -1, 0, 1, -99, 0.638249,0.023487) , 278, 32.4197, 1, 0, 0.56964,0.0632745) , NN( NN( 0, 0, -1, 0, 1, -99, 0.523179,0.00327889) , NN( 0, 0, -1, 0, 1, -99, 0.389728,-0.021057) , 210, 24.3542, 1, 0, 0.475936,-0.0249817) , 270, 18.0478, 1, 0, 0.513977,0.0108479) ); // itree = 95 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.626459,0.026128) , NN( 0, 0, -1, 0, 1, -99, 0.492375,-0.00115277) , 213, 21.7068, 1, 0, 0.540503,0.0401452) , NN( NN( 0, 0, -1, 0, 1, -99, 0.314286,-0.0349141) , NN( 0, 0, -1, 0, 1, -99, 0.506627,0.000568097) , 189, 30.0325, 1, 0, 0.455628,-0.0411362) , 65, 28.3858, 1, 0, 0.492683,-0.00564994) ); // itree = 96 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.386139,-0.0205788) , NN( 0, 0, -1, 0, 1, -99, 0.570529,0.0125471) , 122, 11.9162, 1, 0, 0.549721,0.0407429) , NN( NN( 0, 0, -1, 0, 1, -99, 0.447648,-0.0058905) , NN( 0, 0, -1, 0, 1, -99, 0.186047,-0.0624529) , 38, 52.3033, 1, 0, 0.431624,-0.0434532) , 6, 34.0634, 1, 0, 0.497808,0.0037325) ); // itree = 97 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.505747,0.0036976) , NN( 0, 0, -1, 0, 1, -99, 0.712963,0.0405838) , 124, 35.1235, 1, 0, 0.566396,0.0677544) , NN( NN( 0, 0, -1, 0, 1, -99, 0.417027,-0.0160659) , NN( 0, 0, -1, 0, 1, -99, 0.53958,0.00554792) , 0, 20.9856, 1, 0, 0.474848,-0.0271679) , 4, 20.1552, 1, 0, 0.494943,-0.00633127) ); // itree = 98 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.328767,-0.0270664) , NN( 0, 0, -1, 0, 1, -99, 0.508399,0.00393508) , 246, 25.6982, 1, 0, 0.464135,-0.0168092) , NN( NN( 0, 0, -1, 0, 1, -99, 0.751244,0.039116) , NN( 0, 0, -1, 0, 1, -99, 0.539683,0.00194341) , 37, 32.4511, 1, 0, 0.633554,0.085071) , 219, 45.0658, 1, 0, 0.510989,0.0113665) ); // itree = 99 fBoostWeights.push_back(1); fForest.push_back( NN( NN( NN( 0, 0, -1, 0, 1, -99, 0.362694,-0.0224435) , NN( 0, 0, -1, 0, 1, -99, 0.52286,0.0051675) , 246, 20.8952, 1, 0, 0.500716,0.00603222) , NN( NN( 0, 0, -1, 0, 1, -99, 0.804348,0.0512492) , NN( 0, 0, -1, 0, 1, -99, 0.560976,0.00500233) , 121, 24.4196, 1, 0, 0.689655,0.134685) , 159, 52.6455, 1, 0, 0.521656,0.0202905) ); return; }; // Clean up inline void ReadBDTG::Clear() { for (unsigned int itree=0; itree& inputValues ) const { // classifier response value double retval = 0; // classifier response, sanity check first if (!IsStatusClean()) { std::cout << "Problem in class \"" << fClassName << "\": cannot return classifier response" << " because status is dirty" << std::endl; } else { retval = GetMvaValue__( inputValues ); } return retval; }