feature set 0.0030438540000000004
same feature 0.0028126780000000003
crf training 0.00268804
feature values 0.002628862
simple feature 0.002505157
feature selection 0.002474304
feature functions 0.0024612180000000003
label set 0.002422884
automatic feature 0.002422773
feature induction 0.00237585
feature conjuncts 0.0023737880000000004
training data 0.002257821
label sequence 0.002178104
model decoding 0.002171591
markov model 0.002165895
large label 0.002143748
feature 0.00213631
other label 0.002068785
model example 0.002046993
training time 0.002027424
weak model 0.002009176
component model 0.001996954
order model 0.001954977
label sets 0.001939152
label space 0.001933321
binary label 0.001918419
crf performance 0.001913025
training method 0.001908107
jth model 0.001903572
small label 0.001901916
crf decoding 0.001898741
label distribution 0.001894218
model simi 0.001893677
multiple label 0.001892819
label sequences 0.001888743
label problems 0.001888231
label codes 0.001881045
data set 0.001861035
many features 0.001856513
crf estimation 0.001844583
full label 0.001841605
training methods 0.001834422
single label 0.0018283449999999999
diverse label 0.001798385
label subsets 0.001795549
binary features 0.001787559
binary crf 0.001786789
ing features 0.001781714
standard training 0.001772387
actual label 0.001771169
crf figure 0.001736919
efficient crf 0.001716806
crf algo 0.001713605
traditional crf 0.001712742
dynamic crf 0.001706652
small training 0.001690906
class crf 0.001689421
multiclass crf 0.001685832
training sequences 0.001677733
crf classifiers 0.001674728
crf implementations 0.001671154
model 0.00165656
regular crf 0.001647133
efficient training 0.001637426
crf framework 0.001629129
crf scales 0.001620632
mulated crf 0.001620632
training examples 0.0016054580000000001
training iteration 0.0015991310000000002
current training 0.0015986400000000001
training corpus 0.001590508
mle training 0.00157545
training sentences 0.00157091
training sample 0.001554005
lmvm training 0.001540968
label 0.00151534
test set 0.001418044
conditional log 0.0013933349999999999
features 0.00138448
word length 0.00135696
training 0.00130433
log probability 0.0012626059999999999
current word 0.0012554649999999999
rent word 0.001247062
tagging accuracy 0.001218556
other sequence 0.001216209
word identity 0.001206696
word prefix 0.001198556
sequential data 0.001197023
tabular data 0.001190576
entropy models 0.00117274
binary models 0.001170373
development set 0.001166654
graphical models 0.001154685
conditional random 0.001143246
conditional probability 0.001140557
language problems 0.00113558
generative models 0.001127504
weak models 0.00111991
decoding method 0.001118808
