LEGEND_NAME = Gibbs_LDA

BP_sLDAGibbs_LDAMED_sLDA
PC_sLDAlogistic_regr

LABEL_NAME = more_than_2_out_of_4_stars

more_than_2_out_of_4_stars

FRAC_LABELS = 0.2

0.050.10.2
1.0

N_STATES = 10.0

10.025.050.0
100.0nan
SNAPSHOT_SRCFILE:
/results/bow_pang_movie_reviews_v20170929/20170930-mod_name=slda__np-frac_labels=0.200-n_states=010-alpha=0.1000-tau=0.0100-lambda_w=0.001-init_name=rand_smooth_background-alg_name=mallet_gibbs_sampler-n_batches=1/4/lap0000500.000_topic_model_snapshot

7/10

-3.0


0.999 
schwarzenegger      

0.998 
carrey              

0.998 
goodman             

0.998 
one-liners          

0.998 
film-making         

0.998 
newman              

0.998 
nolte               

0.998 
woo                 

0.998 
snipes              

0.997 
sorvino             

0.997 
quaid               

0.997 
pullman             

0.997 
affleck             

0.997 
seattle             

0.997 
set-up              

5/10

-1.8


1.000 
runtime             

0.998 
psychic             

0.997 
spoiler             

0.997 
accidently          

0.997 
madden              

0.997 
fright              

0.996 
onscreen            

0.996 
antique             

0.996 
permission          

0.996 
thusly              

0.996 
cun                 

0.996 
prone               

0.995 
superbly            

0.995 
upper-class         

0.995 
1947                

1/10

-0.4


1.000 
dialog              

0.999 
***                 

0.999 
email               

0.999 
subscribe           

0.999 
**-1/2              

0.999 
**                  

0.999 
kit                 

0.999 
silicon             

0.998 
****                

0.998 
***-1/2             

0.998 
*-1/2               

0.998 
27                  

0.997 
good-spirited       

0.997 
*                   

0.997 
amc                 

8/10

0.2


1.000 
cops                

0.999 
mob                 

0.999 
robbery             

0.999 
fbi                 

0.999 
casino              

0.999 
niro                

0.999 
del                 

0.999 
sonny               

0.999 
hackman             

0.999 
heist               

0.999 
ransom              

0.999 
denzel              

0.999 
toro                

0.999 
mobster             

0.999 
homicide            

2/10

0.4


1.000 
chan                

1.000 
military            

1.000 
terrorist           

1.000 
colonel             

0.999 
schindler           

0.999 
kilmer              

0.999 
holocaust           

0.999 
hong                

0.999 
nazis               

0.999 
col                 

0.999 
camps               

0.999 
navy                

0.999 
das                 

0.999 
civilian            

0.999 
fort                

3/10

0.8


1.000 
disney              

1.000 
batman              

1.000 
dinosaur            

1.000 
connery             

0.999 
frankenstein        

0.999 
robot               

0.999 
007                 

0.999 
craven              

0.999 
live-action         

0.999 
brosnan             

0.999 
gadget              

0.999 
aladdin             

0.999 
bugs                

0.999 
theron              

0.999 
sequels             

4/10

1.8


1.000 
mom                 

0.999 
santa               

0.999 
brady               

0.998 
middle-class        

0.998 
campus              

0.998 
coming-of-age       

0.998 
claus               

0.998 
pie                 

0.998 
marisa              

0.998 
heels               

0.998 
suburb              

0.997 
working-class       

0.997 
bullies             

0.997 
nerd                

0.996 
mall                

0/10

2.4


1.000 
distributor         

0.999 
classification      

0.999 
ratio               

0.998 
kieslowski          

0.997 
krzysztof           

0.997 
puttnam             

0.997 
point-of-view       

0.997 
goldwyn             

0.997 
ryder               

0.997 
standout            

0.997 
echo                

0.996 
uncertainty         

0.996 
one-hundred         

0.996 
forty               

0.996 
essay               

9/10

2.7


1.000 
woody               

1.000 
dancer              

1.000 
altman              

1.000 
concert             

1.000 
julianne            

0.999 
boxing              

0.999 
disco               

0.999 
beatty              

0.999 
trainspotting       

0.996 
crowe               

0.988 
porn                

0.981 
burt                

0.976 
kane                

0.973 
documentary         

0.966 
kansas              

6/10

4.1


0.999 
branagh             

0.999 
jude                

0.999 
poet                

0.999 
le                  

0.999 
pierre              

0.999 
michel              

0.999 
juliet              

0.999 
italy               

0.999 
romeo               

0.999 
dicaprio            

0.999 
mistress            

0.999 
european            

0.998 
helena              

0.998 
countryside         

0.998 
diary