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

(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 Nikodem Pachala 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 s426135 2020-06-15 13:51 3.0.0 docker lstm 0.7229 0.7618 0.7418 0.8164 0.6750 25
4 Adam Chrzanowski 2020-04-20 13:34 3.0.0 vowpal-wabbit probabilities 0.8340 0.7131 0.7688 0.8170 0.6650 20
5 Szymon Grad 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 Jakub 452101 2020-04-23 08:32 3.0.0 ISI-33, probabilities probabilities 0.6729 0.7718 0.7190 0.8080 0.6586 11
7 Mateusz Mucha 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 Mikolaj Bachorz 2020-04-27 04:03 3.0.0 v2 probabilities 0.6846 0.7483 0.7150 0.8009 0.6482 74
9 Damian Litwin 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 Dominika 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 Lukasz Dawydzik 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 Dawid Majsnerowski 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 Eryk Sokołowski 2020-06-09 10:58 3.0.0 probability probabilities 0.7862 0.7106 0.7465 0.8051 0.6062 22
14 Michał Maciaszek 2020-05-18 13:56 3.0.0 improved naive-bayes multinomial baseline 0.7862 0.7106 0.7465 0.8051 0.6062 14
15 Patryk Dolata 2020-04-25 10:28 3.0.0 bayes prob probabilities 0.7846 0.7068 0.7436 0.8026 0.6035 16
16 Artur Dylewski 2020-06-03 16:27 3.0.0 ISI52 logistic-regression word2vec 0.6223 0.7410 0.6765 0.7828 0.5832 14
17 [anonymised] 2020-06-08 16:50 3.0.0 knn tf knn tf 0.2234 0.8434 0.3532 0.7015 0.5623 45
18 Rafał Piskorski 2020-05-18 14:57 3.0.0 knn-tfidf-v5 knn tf-idf 0.3420 0.8654 0.4903 0.7405 0.5615 13
19 Yevheniia Tsapkova 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 klaganowski 2020-04-27 14:27 3.0.0 Naive Bayes (probabilities) probabilities 0.7777 0.6992 0.7363 0.7968 0.5056 11
22 Dawid Jurkiewicz 2020-05-27 17:42 3.0.0 Stupid solution stupid baseline 0.0000 0.0000 0.0000 0.6351 0.0000 1
23 Anna Maduzia 2020-06-23 22:59 3.0.0 svm ready-made svm 0.6021 0.7685 0.6752 0.7886 0.0000 14
24 Ivan Novgorodtsev 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 Bartosz 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
26 Antoni 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
27 Javier Martinez Jimenez 2020-05-27 17:58 3.0.0 Stupid solution stupid baseline 0.0000 0.0000 0.0000 0.6351 0.0000 2