other model 0.0033761909999999997
good model 0.00316386
different model 0.003143333
order model 0.0031299739999999998
model structure 0.003077425
model type 0.003070468
model parameters 0.003027015
output tag 0.00302086
common model 0.003020485
viterbi model 0.0029441520000000002
appropriate model 0.002942684
model structures 0.002929008
model struc 0.002913182
alternative model 0.00290093
suitable model 0.00289974
der model 0.002893773
model 0.00266607
output tags 0.002179388
new tag 0.0021453239999999997
previous tag 0.002111173
tag operation 0.002092291
output sequence 0.002080162
same output 0.0020167830000000003
current tag 0.002010253
training data 0.0019669180000000002
next tag 0.0019453159999999999
new output 0.001911944
preceding tag 0.001894338
speech tag 0.0018870739999999999
ing output 0.001885766
different output 0.001871003
copy tag 0.00186634
formed tag 0.001855914
output transformation 0.0018285760000000002
output structure 0.001805095
output value 0.001801338
data set 0.00178468
current output 0.001776873
output values 0.001751549
single output 0.0017017960000000002
appropriate output 0.0016703540000000002
output edges 0.001669867
individual output 0.001659729
consecutive output 0.0016573500000000001
output string 0.001655278
output trans 0.001648605
likely output 0.0016481970000000001
output encoding 0.0016470220000000002
adjacent output 0.001646155
output sequences 0.00164577
original output 0.001643904
output struc 0.0016408520000000002
output items 0.001638417
output transformations 0.001636843
suitable output 0.0016274100000000001
ith output 0.00162713
output encod 0.001627116
output val 0.001626564
formed output 0.0016225340000000001
output encodings 0.0016197870000000001
invalid output 0.0016197870000000001
valid output 0.0016197870000000001
reversible output 0.0016197870000000001
output histories 0.001618469
output transfor 0.001618469
specialize output 0.001618469
output alphabet 0.001618469
tem output 0.001618469
test data 0.001588208
previous word 0.001569133
current word 0.001468213
sequence learning 0.001453132
feature set 0.001426004
data sparsity 0.001411291
next word 0.001403276
data problems 0.001397121
output 0.00139374
learning models 0.001386571
testing data 0.0013846940000000001
sparse data 0.001378673
heldout data 0.001375588
learning system 0.001358896
training corpus 0.001325858
rent word 0.001319885
ith word 0.00131847
nth word 0.001314011
new tags 0.0013038519999999999
input feature 0.001289444
input sequence 0.0011846320000000001
such models 0.001183907
many sequence 0.001162021
training example 0.001135734
single training 0.001125064
same input 0.001121253
ing system 0.001084212
order models 0.001083765
feature description 0.001076859
original training 0.001067172
simple search 0.001066535
individual tags 0.001051637
