Skeptic vs paranormal subreddits

Classify a reddit as either from Skeptic subreddit or one of the "paranormal" subreddits (Paranormal, UFOs, TheTruthIsHere, Ghosts, ,Glitch-in-the-Matrix, conspiracytheories). [ver. 3.0.0]

Git repo URL: git://gonito.net/paranormal-or-skeptic / Branch: master
Run git clone --single-branch git://gonito.net/paranormal-or-skeptic -b master to get the challenge data
Browse at https://gonito.net/gitlist/paranormal-or-skeptic.git/master

Leaderboard

# submitter when ver. description test-A Recall test-A Precision test-A F1.0 test-A Accuracy test-A Likelihood ×
1 kubapok 2020-05-13 15:01 3.0.0 roberta large finetuning 1 epoch fairseq (may be finetuned still) 0.8117 0.8417 0.8264 0.8756 0.7525 2
2 [anonymized] 2020-04-22 23:10 3.0.0 Sklearn Logistic regression 1-3gram 1000iter probabilities 0.7011 0.7855 0.7409 0.8210 0.6767 8
3 [anonymized] 2020-06-15 13:51 3.0.0 docker lstm 0.7229 0.7618 0.7418 0.8164 0.6750 25
4 [anonymized] 2020-04-20 13:34 3.0.0 vowpal-wabbit probabilities 0.8340 0.7131 0.7688 0.8170 0.6650 20
5 [anonymized] 2020-04-27 14:45 3.0.0 first test vowpal vowpal-wabbit logistic-regression hyperparam 0.6543 0.7775 0.7106 0.8055 0.6621 22
6 [anonymized] 2020-04-23 08:32 3.0.0 ISI-33, probabilities probabilities 0.6729 0.7718 0.7190 0.8080 0.6586 11
7 [anonymized] 2020-04-26 14:07 3.0.0 Vowpal wabbit hyperparam change vowpal-wabbit logistic-regression hyperparam 0.6319 0.7984 0.7055 0.8075 0.6580 17
8 [anonymized] 2020-04-27 04:03 3.0.0 v2 probabilities 0.6846 0.7483 0.7150 0.8009 0.6482 74
9 [anonymized] 2020-04-21 21:22 3.0.0 NB sklearn with probo probabilities 0.3856 0.8610 0.5327 0.7531 0.6297 9
10 [anonymized] 2020-06-05 13:35 3.0.0 last-branch ready-made xgboost 0.4426 0.8181 0.5744 0.7607 0.6237 14
11 [anonymized] 2020-06-10 00:22 3.0.0 improved splitting naive-bayes multinomial baseline 0.7202 0.7448 0.7323 0.8078 0.6091 17
12 [anonymized] 2020-04-21 16:44 3.0.0 Add Likelihood to ready made NB probabilities 0.7479 0.7173 0.7323 0.8005 0.6074 18
13 [anonymized] 2020-06-09 10:58 3.0.0 probability probabilities 0.7862 0.7106 0.7465 0.8051 0.6062 23
14 [anonymized] 2020-05-18 13:56 3.0.0 improved naive-bayes multinomial baseline 0.7862 0.7106 0.7465 0.8051 0.6062 18
15 [anonymized] 2020-04-25 10:28 3.0.0 bayes prob probabilities 0.7846 0.7068 0.7436 0.8026 0.6035 16
16 [anonymized] 2020-06-03 16:27 3.0.0 ISI52 logistic-regression word2vec 0.6223 0.7410 0.6765 0.7828 0.5832 14
17 [anonymized] 2020-06-08 16:50 3.0.0 knn tf knn tf 0.2234 0.8434 0.3532 0.7015 0.5623 45
18 [anonymized] 2020-05-18 14:57 3.0.0 knn-tfidf-v5 knn tf-idf 0.3420 0.8654 0.4903 0.7405 0.5615 14
19 [anonymized] 2020-06-07 13:54 3.0.0 tf idf solution knn tf-idf 0.1319 0.9118 0.2305 0.6786 0.5547 11
20 p/tlen 2020-04-20 13:18 3.0.0 To probabilities null-model baseline 0.1048 0.8914 0.1875 0.6687 0.5282 4
21 [anonymized] 2020-04-27 14:27 3.0.0 Naive Bayes (probabilities) probabilities 0.7777 0.6992 0.7363 0.7968 0.5056 11
22 [anonymized] 2020-05-27 17:42 3.0.0 Stupid solution stupid baseline 0.0000 0.0000 0.0000 0.6351 0.0000 1
23 [anonymized] 2020-06-23 22:59 3.0.0 svm ready-made svm 0.6021 0.7685 0.6752 0.7886 0.0000 14
24 [anonymized] 2020-06-30 22:44 3.0.0 Upload files to 'test-A' self-made linear-regression gradient-descent 0.3362 0.5351 0.4129 0.6512 0.0000 11
25 [anonymized] 2020-12-16 11:46 3.0.0 working logistic-regression pytorch-nn 0.1729 0.3714 0.2359 0.5914 0.0000 1
26 [anonymized] 2020-06-09 20:02 3.0.0 Use Linear Regression V6 self-made linear-regression gradient-descent 0.4803 0.5953 0.5316 0.6912 0.0000 44
27 [anonymized] 2020-05-04 13:16 3.0.0 linear regression gradient descent self-made linear-regression gradient-descent 0.3660 0.7845 0.4991 0.7319 0.0000 22
28 [anonymized] 2020-05-27 17:58 3.0.0 Stupid solution stupid baseline 0.0000 0.0000 0.0000 0.6351 0.0000 2
29 [anonymized] 2020-12-16 10:53 3.0.0 4 iteracje 0.1691 0.3693 0.2320 0.5914 0.0000 5
30 [anonymized] 2020-12-16 08:41 3.0.0 Moje genialne rozwiazanie logistic-regression pytorch-nn 0.0436 0.4000 0.0787 0.6271 0.0000 3
31 [anonymized] 2021-02-18 20:19 3.0.0 update + out, final logistic-regression pytorch-nn 0.1734 0.3730 0.2367 0.5920 0.0000 2
32 [anonymized] 2021-02-17 19:59 3.0.0 paranormal logistic-regression pytorch-nn 0.1729 0.3706 0.2358 0.5910 0.0000 2
33 Marcin Kostrzewski 2022-05-10 22:01 3.0.0 Add predictions naive-bayes 0.3718 0.7327 0.4933 0.7213 0.0000 1
34 Martyna Druminska 2022-05-28 13:44 3.0.0 my brilliant self-made neural-network word2vec pytorch-nn 0.4287 0.7133 0.5355 0.7286 0.0000 3
35 s444417 2022-05-18 08:59 3.0.0 fix output naive-bayes 0.6213 0.5458 0.5811 0.6731 0.0000 7
36 s443930 2022-06-22 21:37 3.0.0 s443930 transformer 0.4723 0.6794 0.5573 0.7261 0.0000 4
37 s409771 2022-05-25 20:59 3.0.0 first solution neural-network word2vec 0.5181 0.7356 0.6080 0.7562 0.0000 2
38 s478815 2022-06-14 22:10 3.0.0 478815 neural-network word2vec 0.5830 0.7282 0.6476 0.7684 0.0000 3
39 [anonymized] 2022-06-22 08:12 3.0.0 s478874 transformer 0.8027 0.6087 0.6924 0.7397 0.0000 6
40 ked 2022-05-24 21:35 3.0.0 s449288 - simple NN with GloVe vectors neural-network word2vec 0.6096 0.6945 0.6493 0.7597 0.0000 3
41 Cezary 2022-05-25 21:10 3.0.0 s470623 neural-network word2vec 0.4819 0.7067 0.5731 0.7380 0.0000 1
42 [anonymized] 2022-05-27 15:37 3.0.0 478841 results neural-network word2vec 0.6037 0.7143 0.6544 0.7673 0.0000 3
43 Jakub 2022-06-08 09:09 3.0.0 s434624 neural-network word2vec 0.0229 0.4433 0.0435 0.6330 0.0000 1
44 [anonymized] 2022-05-24 09:15 3.0.0 s478831 neural-network word2vec 0.6144 0.6082 0.6113 0.7149 0.0000 1
45 s444498 2022-05-11 21:45 3.0.0 s444498 naive-bayes 0.3223 0.7690 0.4543 0.7174 0.0000 2
46 Mikołaj Pokrywka 2022-05-24 21:43 3.0.0 s444463 neural-network word2vec 0.5197 0.7797 0.6237 0.7712 0.0000 2
47 s444517 2022-05-23 15:13 3.0.0 s444517 - PyTorch feed forward neural network self-made neural-network word2vec 0.3973 0.7155 0.5109 0.7224 0.0000 2
48 s478855 2022-06-22 11:35 3.0.0 s478855 - correct outs transformer 0.7234 0.7572 0.7399 0.8144 0.0000 3
49 s478840 2022-06-21 21:00 3.0.0 s478840 transformer 0.6468 0.6441 0.6454 0.7407 0.0000 5
50 s478846 2022-05-24 09:45 3.0.0 First solution neural-network word2vec 0.6766 0.7374 0.7057 0.7941 0.0000 1
51 s444356 2022-05-09 18:46 3.0.0 s444356 naive-bayes 0.3718 0.7327 0.4933 0.7213 0.0000 1
52 s444501 2022-05-10 14:11 3.0.0 s444501 naive-bayes 0.2968 0.8242 0.4364 0.7203 0.0000 1
53 Kamil Guttmann 2022-05-23 19:32 3.0.0 s444380 simple nn + word2vec neural-network word2vec 0.4676 0.7343 0.5713 0.7440 0.0000 3
54 [anonymized] 2022-05-08 20:10 3.0.0 444421 naive-bayes 0.2734 0.7823 0.4052 0.7071 0.0000 1
55 s444465 2022-05-23 14:54 3.0.0 s444465 neural-network word2vec 0.6059 0.7363 0.6647 0.7770 0.0000 2
56 s444018 2022-05-10 22:21 3.0.0 s444018 naive-bayes self-made 0.3835 0.8857 0.5353 0.7570 0.0000 2
57 Adam Wojdyła 2022-06-01 21:08 3.0.0 4444507 neural-network word2vec 0.4654 0.7184 0.5649 0.7384 0.0000 4
58 [anonymized] 2022-06-06 21:43 3.0.0 out dev neural-network word2vec 0.5229 0.7352 0.6111 0.7572 0.0000 1