Index

A

AbstractLossFunction (class in hep_ml.losses) AbstractNeuralNetworkClassifier (class in hep_ml.nnet)

AbstractNeuralNetworkRegressor (class in hep_ml.nnet) adadelta_trainer() (in module hep_ml.nnet) AdaLossFunction (class in hep_ml.losses)

B

BinBasedCvM (class in hep_ml.metrics) BinBasedSDE (class in hep_ml.metrics) BinBasedTheil (class in hep_ml.metrics)

BinFlatnessLossFunction (class in hep_ml.losses) BinsReweighter (class in hep_ml.reweight) BinTransformer (class in hep_ml.preprocessing)

C

check_dimensions() (hep_ml.speedup.LookupClassifier method) CompositeLossFunction (class in hep_ml.losses) compute_bin_indices() (hep_ml.reweight.BinsReweighter method) compute_optimal_step() (hep_ml.losses.AbstractLossFunction method) (hep_ml.losses.MAELossFunction method) (hep_ml.losses.MSELossFunction method)

compute_parameters() (hep_ml.losses.KnnAdaLossFunction method) compute_sweights() (in module hep_ml.splot) convert_bins_to_lookup_index() (hep_ml.speedup.LookupClassifier method) convert_lookup_index_to_bins() (hep_ml.speedup.LookupClassifier method)

D

decision_function() (hep_ml.uboost.uBoostBDT method)

E

exp_log_loss() (in module hep_ml.nnet)

exp_loss() (in module hep_ml.nnet)

F

feature_importances_ (hep_ml.uboost.uBoostBDT property) fit() (hep_ml.gradientboosting.UGradientBoostingClassifier method) (hep_ml.gradientboosting.UGradientBoostingRegressor method) (hep_ml.losses.AbstractLossFunction method) (hep_ml.losses.AdaLossFunction method) (hep_ml.losses.CompositeLossFunction method) (hep_ml.losses.LogLossFunction method) (hep_ml.losses.MAELossFunction method) (hep_ml.losses.MSELossFunction method) (hep_ml.losses.RankBoostLossFunction method) (hep_ml.losses.ReweightLossFunction method) (hep_ml.nnet.AbstractNeuralNetworkClassifier method) (hep_ml.nnet.AbstractNeuralNetworkRegressor method) (hep_ml.preprocessing.BinTransformer method) (hep_ml.preprocessing.IronTransformer method) (hep_ml.reweight.BinsReweighter method) (hep_ml.reweight.FoldingReweighter method) (hep_ml.reweight.GBReweighter method) (hep_ml.speedup.LookupClassifier method) (hep_ml.uboost.uBoostBDT method) (hep_ml.uboost.uBoostClassifier method)

FoldingReweighter (class in hep_ml.reweight)

G

GBReweighter (class in hep_ml.reweight)

H

hep_ml.gradientboosting module hep_ml.losses module hep_ml.metrics module hep_ml.nnet module hep_ml.preprocessing module hep_ml.reweight module

hep_ml.speedup module hep_ml.splot module hep_ml.uboost module hessian() (hep_ml.losses.AdaLossFunction method) (hep_ml.losses.CompositeLossFunction method) (hep_ml.losses.LogLossFunction method) (hep_ml.losses.MSELossFunction method) (hep_ml.losses.RankBoostLossFunction method)

I

IronTransformer (class in hep_ml.preprocessing)

irprop_minus_trainer() (in module hep_ml.nnet) irprop_plus_trainer() (in module hep_ml.nnet)

K

KnnAdaLossFunction (class in hep_ml.losses) KnnBasedCvM (class in hep_ml.metrics)

KnnBasedSDE (class in hep_ml.metrics) KnnBasedTheil (class in hep_ml.metrics) KnnFlatnessLossFunction (class in hep_ml.losses)

L

log_loss() (in module hep_ml.nnet)

LogLossFunction (class in hep_ml.losses) LookupClassifier (class in hep_ml.speedup)

M

MAELossFunction (class in hep_ml.losses) MLPClassifier (class in hep_ml.nnet) MLPMultiClassifier (class in hep_ml.nnet) MLPRegressor (class in hep_ml.nnet) module hep_ml.gradientboosting hep_ml.losses hep_ml.metrics hep_ml.nnet hep_ml.preprocessing hep_ml.reweight hep_ml.speedup hep_ml.splot hep_ml.uboost

mse_loss() (in module hep_ml.nnet) MSELossFunction (class in hep_ml.losses)

N

negative_gradient() (hep_ml.losses.AdaLossFunction method) (hep_ml.losses.CompositeLossFunction method) (hep_ml.losses.LogLossFunction method) (hep_ml.losses.MAELossFunction method) (hep_ml.losses.MSELossFunction method) (hep_ml.losses.RankBoostLossFunction method) (hep_ml.losses.ReweightLossFunction method)

P

PairwiseNeuralNetwork (class in hep_ml.nnet) PairwiseSoftplusNeuralNetwork (class in hep_ml.nnet) predict() (hep_ml.gradientboosting.UGradientBoostingClassifier method) (hep_ml.gradientboosting.UGradientBoostingRegressor method) (hep_ml.nnet.AbstractNeuralNetworkClassifier method) (hep_ml.nnet.AbstractNeuralNetworkRegressor method) (hep_ml.speedup.LookupClassifier method) (hep_ml.uboost.uBoostBDT method) (hep_ml.uboost.uBoostClassifier method) predict_proba() (hep_ml.gradientboosting.UGradientBoostingClassifier method) (hep_ml.nnet.AbstractNeuralNetworkClassifier method) (hep_ml.speedup.LookupClassifier method) (hep_ml.uboost.uBoostBDT method) (hep_ml.uboost.uBoostClassifier method)

predict_weights() (hep_ml.reweight.BinsReweighter method) (hep_ml.reweight.FoldingReweighter method) (hep_ml.reweight.GBReweighter method) prepare_new_leaves_values() (hep_ml.losses.AbstractLossFunction method) (hep_ml.losses.MAELossFunction method) (hep_ml.losses.RankBoostLossFunction method) (hep_ml.losses.ReweightLossFunction method) prepare_tree_params() (hep_ml.losses.AbstractLossFunction method) (hep_ml.losses.AdaLossFunction method) (hep_ml.losses.LogLossFunction method) (hep_ml.losses.MAELossFunction method) (hep_ml.losses.MSELossFunction method) (hep_ml.losses.ReweightLossFunction method)

R

RankBoostLossFunction (class in hep_ml.losses)

RBFNeuralNetwork (class in hep_ml.nnet) ReweightLossFunction (class in hep_ml.losses)

S

sgd_trainer() (in module hep_ml.nnet) SimpleNeuralNetwork (class in hep_ml.nnet) smooth_huber_loss() (in module hep_ml.nnet) SoftmaxNeuralNetwork (class in hep_ml.nnet) squared_loss() (in module hep_ml.nnet)

staged_decision_function() (hep_ml.uboost.uBoostBDT method) staged_predict() (hep_ml.gradientboosting.UGradientBoostingRegressor method) staged_predict_proba() (hep_ml.gradientboosting.UGradientBoostingClassifier method) (hep_ml.uboost.uBoostBDT method) (hep_ml.uboost.uBoostClassifier method)

T

transform() (hep_ml.preprocessing.BinTransformer method) (hep_ml.preprocessing.IronTransformer method) (hep_ml.speedup.LookupClassifier method)

U

uBoostBDT (class in hep_ml.uboost) uBoostClassifier (class in hep_ml.uboost)

UGradientBoostingClassifier (class in hep_ml.gradientboosting) UGradientBoostingRegressor (class in hep_ml.gradientboosting)