LEGEND_NAME = PC_sLDA
LABEL_NAME = delivery
FRAC_LABELS = 0.1
N_STATES = 10.0
SNAPSHOT_SRCFILE:
/results/yelp_7label/20171011frombest-mod_name=slda__tf-frac_labels=0.100-n_states=010-alpha=1.1000-tau=1.0100-lambda_w=000.100-init_name=bestauc_gibbs_K010_f0.100-weight_x=1.0-weight_y=1000.0-qinit=0.1-decay_rate=adam-step_size=0.1000-n_batches=10/1/lap0000005.000_topic_model_snapshot
3/10 -3.2
1.000 fixe
1.000 summerlicious
1.000 winterlicious
0.999 giada
0.999 fingerling
0.999 agnolotti
0.999 jaleo
0.999 sweetbreads
0.999 delmonico
0.999 escargots
0.998 friscos
0.998 iberico
0.998 fiamma
0.998 stripsteak
0.998 endive
|
2/10 -3.2
1.000 smashburger
1.000 culvers
1.000 portillos
1.000 primantis
1.000 freddys
1.000 montagu
1.000 teds
0.999 burgatory
0.999 dickeys
0.999 slymans
0.999 lucilles
0.999 fukuburger
0.999 capastrami
0.999 tessaros
0.999 montague
|
6/10 -2.8
1.000 wynn
1.000 aria
1.000 mgm
1.000 bacchanal
1.000 mandalay
1.000 bellagio
1.000 casinos
1.000 luxor
1.000 palazzo
1.000 ballys
1.000 harrahs
1.000 sls
1.000 bellagios
0.999 wynns
0.999 rodizio
|
9/10 -2.4
1.000 zipps
1.000 breweries
1.000 bww
1.000 kilt
1.000 darts
1.000 hofbrauhaus
1.000 hoppy
0.999 shuffleboard
0.999 cornhole
0.999 brewpub
0.999 trivia
0.999 brewers
0.999 topgolf
0.999 growler
0.999 hannys
|
5/10 -2.1
1.000 benedicts
1.000 amelies
1.000 pamelas
0.999 quiches
0.999 scrambler
0.999 dupars
0.999 jamms
0.999 scone
0.999 kneaders
0.999 einsteins
0.999 mimis
0.998 hotcakes
0.998 baristas
0.998 bagels
0.998 barista
|
7/10 -1.7
1.000 salsas
1.000 asada
1.000 pastor
1.000 relleno
1.000 arepa
1.000 fundido
1.000 arepas
1.000 tortas
1.000 lengua
1.000 pupusas
1.000 machaca
1.000 adobada
1.000 chimi
1.000 flautas
1.000 enchiladas
|
1/10 -1.4
1.000 und
1.000 der
1.000 auch
1.000 sehr
1.000 ich
1.000 nicht
1.000 wir
1.000 mit
1.000 ein
1.000 essen
1.000 aber
1.000 für
1.000 une
1.000 auf
1.000 waren
|
8/10 -0.9
1.000 nigiri
1.000 bulgogi
1.000 hibachi
1.000 maki
1.000 bibimbap
1.000 kbbq
1.000 banchan
1.000 unagi
1.000 teppanyaki
1.000 chirashi
1.000 soju
1.000 okonomiyaki
1.000 musubi
1.000 teppan
1.000 yakitori
|
0/10 0.7
1.000 paneer
1.000 curries
1.000 panang
1.000 biryani
1.000 khao
1.000 samosa
1.000 szechuan
1.000 lassi
1.000 vindaloo
1.000 kha
1.000 saag
1.000 korma
1.000 malaysian
1.000 thali
1.000 aloo
|
4/10 3.3
1.000 calzone
1.000 calzones
1.000 shwarma
1.000 rosatis
1.000 schwarma
1.000 spinatos
1.000 aladdins
1.000 nypd
1.000 stromboli
1.000 saganaki
1.000 moussaka
1.000 settebello
1.000 koobideh
1.000 pizzerias
1.000 nellos
|