Cluster Polish urban legend texts

Cluster Polish urban legend texts the way folklorists do. [ver. 1.0.0]

# submitter when ver. description dev-0 NMI test-A NMI
24 [anonymised] 2017-06-05 15:44 1.0.0 normalizacja vol3, dodanie pliku kmeans2.py 0.6641120445586982 0.725198911237184
23 [anonymised] 2017-06-05 15:42 1.0.0 normalizacja vol3, dodanie pliku kmeans.py k-means 0.6641120445586982 0.725198911237184
39 [anonymised] 2017-06-05 15:36 1.0.0 normalizacja vol3, dodanie pliku kmeans.py 0.6860366207079274 0.6370441548849237
12 [anonymised] 2017-06-04 14:19 1.0.0 ver1 python ready-made k-means N/A 0.7661876348886398
4 [anonymised] 2017-04-08 23:30 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method, with stopwords, silly "stem" 0.6819651062442174 0.8363680525690848
2 [anonymised] 2017-04-08 23:26 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method, with stopwords, silly "stem" 0.6648013380341287 0.8502615000174009
1 [anonymised] 2017-04-08 23:21 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method, with stopwords, silly "stem" python self-made k-means 0.6803747241423944 0.8572291518635689
3 [anonymised] 2017-04-08 23:20 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method, with stopwords, silly "stem" 0.7093359271301919 0.8386703415534659
5 [anonymised] 2017-04-08 22:45 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method, with stopwords, stemmed with stempel python self-made 0.669673757100901 0.8043141668771794
6 [anonymised] 2017-04-08 22:43 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method, with stopwords, stemmed with stempel 0.7003945651468501 0.7818413876696954
38 [anonymised] 2017-04-08 22:36 1.0.0 bezosobowo v2 0.6925516594392771 0.6370441548849237
37 [anonymised] 2017-04-08 22:34 1.0.0 bezosobowo v1 0.6860181676217268 0.6431710167511843
34 [anonymised] 2017-04-08 22:25 1.0.0 normalizacja vol9 k-means 0.6888944811430445 0.6636071426947387
51 [anonymised] 2017-04-08 22:23 1.0.0 normalizacja vol8 0.6226236126001983 0.4383496001775261
35 [anonymised] 2017-04-08 22:14 1.0.0 parametry vol8 0.6994303289921318 0.6566253274048532
41 [anonymised] 2017-04-08 22:12 1.0.0 parametry vol7 0.6784258330266995 0.6131434972327906
36 [anonymised] 2017-04-08 22:09 1.0.0 parametry vol6 0.6412291748018083 0.6436939870190814
27 [anonymised] 2017-04-08 22:07 1.0.0 parametry vol5 0.6791281743571093 0.7112280072929971
22 [anonymised] 2017-04-08 22:06 1.0.0 parametry vol4 0.6791281743571096 0.7254145120173199
21 [anonymised] 2017-04-08 22:05 1.0.0 parametry vol3 k-means 0.6641120445586981 0.7256574023468709
28 [anonymised] 2017-04-08 22:03 1.0.0 parametry vol2 0.6703107514350614 0.7076750286002943
30 [anonymised] 2017-04-08 22:01 1.0.0 parametry vol1 0.712311181463451 0.7032417861802746
16 [anonymised] 2017-04-08 22:00 1.0.0 test23 N/A 0.7525558102510004
13 [anonymised] 2017-04-08 22:00 1.0.0 test22 N/A 0.76506435223652
9 [anonymised] 2017-04-08 21:59 1.0.0 test21 N/A 0.7727240355098017
40 [anonymised] 2017-04-08 21:59 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method, with stopwords, stemmed with stempel python self-made 0.8108488650175038 0.6311174364125615
11 [anonymised] 2017-04-08 21:58 1.0.0 test20 N/A 0.7686236548680393
10 [anonymised] 2017-04-08 21:58 1.0.0 test19 N/A 0.7704728669288838
50 [anonymised] 2017-04-08 21:57 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method, with stopwords, stemmed with stempel 0.612345911495219 0.43850562786776626
15 [anonymised] 2017-04-08 21:57 1.0.0 test18 N/A 0.7553315504755335
7 [anonymised] 2017-04-08 21:56 1.0.0 test17 k-means N/A 0.774448924903754
54 [anonymised] 2017-04-08 21:56 1.0.0 normalizacja vol3 0.5731522866057539 0.4221557449019918
8 [anonymised] 2017-04-08 21:55 1.0.0 test16 N/A 0.7732666505010413
14 [anonymised] 2017-04-08 21:54 1.0.0 test15 N/A 0.7585787066638439
17 [anonymised] 2017-04-08 21:53 1.0.0 test 14 N/A 0.7517518694326962
18 [anonymised] 2017-04-08 21:52 1.0.0 test13 N/A 0.7513798284851543
31 [anonymised] 2017-04-08 21:51 1.0.0 test12 N/A 0.6896885498866929
19 [anonymised] 2017-04-08 21:50 1.0.0 test11 N/A 0.7494799841643507
53 [anonymised] 2017-04-08 21:49 1.0.0 test10 N/A 0.42716076199884595
25 [anonymised] 2017-04-08 21:48 1.0.0 test9 N/A 0.7231681457851038
26 [anonymised] 2017-04-08 21:47 1.0.0 test8 N/A 0.7227188669889255
29 [anonymised] 2017-04-08 21:46 1.0.0 test7 N/A 0.7035814928616418
32 [anonymised] 2017-04-08 21:45 1.0.0 test6 N/A 0.6775900329008118
33 [anonymised] 2017-04-08 21:44 1.0.0 test5 N/A 0.6695197387554171
42 [anonymised] 2017-04-08 21:42 1.0.0 test4 N/A 0.6016830746788923
44 [anonymised] 2017-04-08 21:40 1.0.0 test3 N/A 0.5735621842938592
47 [anonymised] 2017-04-08 21:38 1.0.0 test 2 N/A 0.5134718324451454
48 [anonymised] 2017-04-08 21:35 1.0.0 normalizacja vol2 0.6672042420586912 0.49300219099093795
49 [anonymised] 2017-04-08 21:35 1.0.0 test N/A 0.4527400993100195
52 [anonymised] 2017-04-08 21:10 1.0.0 normalizacja vol1 0.6498809182532715 0.43580389279809945
46 [anonymised] 2017-04-08 20:31 1.0.0 test 0.5312920471595906 0.5256551832074122
43 [anonymised] 2017-04-08 19:45 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method (K≅16), with stopwords, silly "stem" python self-made 0.8373352752476644 0.5881295779548537
45 [anonymised] 2017-04-08 19:42 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method (K≅13), with stopwords, silly "stem" 0.8148725590211685 0.547713348357848
57 [anonymised] 2017-04-08 19:40 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method (K≅8), with stopwords, silly "stem" 0.6934862017762761 0.32757312335854644
56 [anonymised] 2017-04-08 19:36 1.0.0 k-medoids, k-means++ initialization, cosine similarity, tf-idf, elbow method (K≅10), with stopwords, silly "stem" 0.8301887650889045 0.389981887625358
55 [anonymised] 2017-04-08 12:56 1.0.0 k-medoids, k-means++ initialization, euclidean distance, tf-idf, elbow method (K≅11), with stopwords, silly "stem" python self-made 0.8276508148065742 0.41562595291857507
58 [anonymised] 2017-04-08 12:40 1.0.0 k-medoids, k-means++ initialization, tf-idf, elbow method (K≅8), without stopwords, silly "stem" python self-made 0.7550669619647504 0.32496544673203104
20 p/tlen 2017-03-26 20:15 1.0.0 stupid solution... stupid 0.6568363109561032 0.7387854240025928