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