antystenes 
20170529 15:18

Basic linear regression haskell linearregression selfmade 
85.0

85.4


EmEm 
20170528 13:55

50 ep ,00001 lr, 18142014 linearregression selfmade 
N/A

93.3


EmEm 
20170519 19:18

20 ep ,00005 lr 
N/A

396.9


EmEm 
20170519 18:52

10 ep ,0001 lr linearregression selfmade 
N/A

393.3


[anonymised] 
20160611 14:29

Max entropy solution for 4 grams and 5 class 
31.5

41.0


[anonymised] 
20160611 14:09

neural network, 4grams, 8 class 
31.5

41.0


[anonymised] 
20160611 14:03

GLM 
31.5

41.0


[anonymised] 
20160611 13:16

GLM solution for 4 grams and 8 class 
31.5

41.0


R.J. 
20160529 14:08

VW nn 6 on up to 4grams and [57] tokens + wiki years 
17.1

24.9


R.J. 
20160529 10:35

Wiki years  min year from article, with [1842013] 
81.8

82.9


R.J. 
20160529 08:21

Wiki years 
103.1

N/A


R.J. 
20160529 07:48

Wiki years 
103.1

N/A


R.J. 
20160525 13:13

VW nn 6 on up to 5grams and [68] tokens 
17.9

26.4


R.J. 
20160525 11:40

Current best solution with changed learning rate 
17.3

25.5


[anonymised] 
20160513 13:21

Max entropy solution for 4 grams and 8 class 
26.6

35.8


[anonymised] 
20160513 13:16

Solution for 4grams and 8 class 
24.7

36.8


[anonymised] 
20160507 21:29

Solution for 4grams and 10 class 
24.7

37.4


[anonymised] 
20160507 21:25

Solution for 4grams and 20 class 
25.1

38.4


[anonymised] 
20160430 18:20

Solution for 4grams and 40 class 
26.7

40.3


[anonymised] 
20160429 20:21

Solution for 4grams and 67 class 
27.3

41.6


[anonymised] 
20160429 07:27

Solution for 4grams and 100 class 
28.4

41.8


[anonymised] 
20160422 11:32

Solution for 4grams 
30.2

43.2


[anonymised] 
20160420 12:19

Solution 
30.2

44.6


[anonymised] 
20160107 07:56

Po najczęściej występujących słowach 
N/A

N/A


p/tlen 
20151219 11:07

VW classifier (10year chronon) 
24.5

34.4


[anonymised] 
20151216 23:38

first submission 
N/A

75.0


Marcin JunczysDowmunt 
20151216 20:40

another try with more bits 
16.7

27.2


[anonymised] 
20151216 20:13

+ script 
34.7

50.3


[anonymised] 
20151214 08:01

tfidf, min_df = 3 
34.7

50.3


[anonymised] 
20151213 22:16

test with min_df = 3 
41.5

60.1


Marcin JunczysDowmunt 
20151213 18:50

Simple 2layer network with up to 4 chars ngrams 
16.8

27.6


p/tlen 
20151213 14:31

VW nn 6 on up to 4grams and [57] tokens vowpalwabbit neuralnetwork 
17.2

24.8


p/tlen 
20151213 12:50

VW nn 6 on up to 4grams and [58] tokens 
17.2

25.3


p/tlen 
20151213 12:49

VW nn 6 on up to 4grams and [58] tokens 
45.9

46.5


[anonymised] 
20151213 11:52

Corrected better solution 
31.9

44.4


[anonymised] 
20151213 11:43

Maybe better solution 
N/A

44.4


Marcin JunczysDowmunt 
20151212 22:02

The same as last, best epoch 
16.3

24.9


[anonymised] 
20151212 15:56

test samego dev0 dla okrojonego treningu 
61.5

N/A


p/tlen 
20151212 15:12

up to 4grams (VW with nn 6 found with vwhypersearch) 
17.2

25.5


p/tlen 
20151212 15:10

up to 4grams (VW with nn 6 found with vwhypersearch) 
45.9

46.5


Marcin JunczysDowmunt 
20151211 19:49

Same as lat, word2vec pretraining 
16.4

25.3


Marcin JunczysDowmunt 
20151211 19:37

200 hidden units in GRU, more epochs, full batches 
17.5

27.3


[anonymised] 
20151211 16:32

First solution 
30.2

44.6


p/tlen 
20151210 21:15

up to 4grams (VW with nn 10) 
17.7

26.0


Marcin JunczysDowmunt 
20151209 08:46

900 words, more units, RMSprop 
18.5

27.5


p/tlen 
20151208 20:18

signi tempori (with poor man's stemming by taking the first 7 letters) 
48.1

50.2


Marcin JunczysDowmunt 
20151207 21:26

Better regression layer, 10 year bins weighted average 
19.6

30.0


Marcin JunczysDowmunt 
20151207 14:58

just one epoch, to avoid overfitting 
23.3

33.8


Marcin JunczysDowmunt 
20151207 14:50

Much simpler model, less hidden units, l2=1e5 
20.8

31.7


Marcin JunczysDowmunt 
20151207 09:20

now with better regularization 
20.9

31.6


Marcin JunczysDowmunt 
20151204 22:47

Neural Network, first try 
22.0

30.2


p/tlen 
20151125 22:29

up to 4grams 
19.6

28.4


p/tlen 
20151125 22:27

up to 4grams 
45.9

46.5


p/tlen 
20151125 20:47

5grams 
22.0

33.5


p/tlen 
20151125 20:05

birth years 
57.4

56.7


p/tlen 
20151124 22:23

handcrafted rules 
46.6

50.9


p/tlen 
20151124 21:40

by known words 
57.9

56.5


p/tlen 
20151124 20:24

by year references 
45.9

46.5


p/tlen 
20151124 19:59

null model with a half year 
57.9

57.7


p/tlen 
20151124 19:58

null model 
57.9

57.7


p/tlen 
20151114 16:30

test 
81.1

57.7

