Index

A

Activation (class in refann.sequence)

activation() (in module refann.element) ANN (class in refann.refann)

B

BatchNorm (class in refann.sequence)

C

call_GPU() (refann.train.Train method)

cuda2numpy() (in module refann.data_process) cuda2torch() (in module refann.data_process)

D

decreasingNode() (in module refann.nodeframe)

default() (in module refann.hpmodel) Dropout (class in refann.sequence)

E

elu() (in module refann.element)

exp() (refann.optimize.LrDecay method)

F

FcNet (class in refann.fcnet)

forward() (refann.fcnet.FcNet method)

G

get_FcNet() (in module refann.fcnet) get_optimal() (refann.refann.OptimizeANN method)

get_risk() (refann.refann.OptimizeANN method) get_seq() (refann.sequence.LinearSeq method)

I

inverseNorm() (refann.data_process.InverseNormalize method)

InverseNormalize (class in refann.data_process)

L

leakyrelu() (in module refann.element) LinearSeq (class in refann.sequence)

load_net() (refann.refann.RePredictANN method) loss_funcs() (in module refann.train) LrDecay (class in refann.optimize)

M

mean (refann.data_process.Statistic attribute) mean() (refann.data_process.InverseNormalize method) (refann.data_process.Normalize method)

minmax() (refann.data_process.InverseNormalize method) (refann.data_process.Normalize method) mkdir() (in module refann.save) models() (in module refann.hpmodel)

N

norm() (refann.data_process.Normalize method) Normalize (class in refann.data_process)

nuisance_hp() (in module refann.hpmodel) numpy2cuda() (in module refann.data_process) numpy2torch() (in module refann.data_process)

O

OptimizeANN (class in refann.refann)

P

plot_func() (refann.refann.ANN method) plot_loss() (in module refann.evaluate) (refann.refann.ANN method) plot_risk() (refann.refann.OptimizeANN method)

poly() (refann.optimize.LrDecay method) Pooling (class in refann.sequence) predict() (in module refann.evaluate) (refann.refann.ANN method) prelu() (in module refann.element)

R

rec_1() (in module refann.hpmodel) rec_2() (in module refann.hpmodel) refann.data_process (module) refann.element (module) refann.evaluate (module) refann.fcnet (module) refann.hpmodel (module) refann.nodeframe (module) refann.optimize (module)

refann.refann (module) refann.save (module) refann.sequence (module) refann.train (module) relu() (in module refann.element) RePredictANN (class in refann.refann) risk() (refann.refann.OptimizeANN method) rrelu() (in module refann.element) rss() (refann.refann.OptimizeANN method)

S

save_func() (refann.refann.ANN method) save_net() (refann.refann.ANN method) savenpy() (in module refann.save) savetxt() (in module refann.save) seq_name() (refann.sequence.SeqName method)

SeqName (class in refann.sequence) Statistic (class in refann.data_process) statistic() (refann.data_process.Statistic method) (refann.refann.ANN method) std (refann.data_process.Statistic attribute) step() (refann.optimize.LrDecay method)

T

torch2cuda() (in module refann.data_process) torch2numpy() (in module refann.data_process) Train (class in refann.train) train() (refann.refann.ANN method)

train_0() (refann.train.Train method) train_1() (refann.train.Train method) transfer_data() (refann.train.Train method) transfer_net() (refann.train.Train method) triangleNode_1() (in module refann.nodeframe)

X

xmax (refann.data_process.Statistic attribute)

xmin (refann.data_process.Statistic attribute)

Z

z_score() (refann.data_process.InverseNormalize method) (refann.data_process.Normalize method)