MLcomp version alpha Statistics: 1213 users, 402 datasets, 328 programs, 9938 runs (0 queued, 0 running), 0 workers

movielens1m

1M MovieLens movie ratings dataset from http://www.grouplens.org/. The original dataset contains 1,000,209 anonymous ratings (1-5 stars) of approximately 3,900 movies made by 6,040 MovieLens users who joined MovieLens in 2000. This sub-dataset includes the ratings of 5,000 randomly selected users. A single rating from each user was withheld to form the test set. See included README.txt for more information.

Format:	CollaborativeFiltering
User:	lester
Size:	32M
Status:	processed
Access:	restricted_access
#train	830307
#test	5000
#rows	5000
#cols	0
minY
maxY

Run a program on this dataset

Select a program CollaborativeFiltering 1-25 of 107 < > Filter:

	Name	Created	User	Rating <<	#runs
run	xterm-knnsvd_shrunk_unbias_rev-r	2y84d ago	xterm	61	6
run	MyMediaLite-slopeone	217d21h ago	zenogantner	61	6
run	mean_user_rating_ruby	2y109d ago	jake	61	6
run	mean_movie_rating_ruby	2y105d ago	jake	61	6
run	MyMediaLite-user-item-baseline	216d18h ago	zenogantner	60	16
run	jjariyas-svdj-r	2y88d ago	jjariyas	60	6
run	nanhengwu-mf_for1m2-r	2y87d ago	nanhengwu	60	7
run	MyMediaLite-matrix-factorization-k-10	217d3h ago	zenogantner	60	19
run	MyMediaLite-matrix-factorization-k-20	217d3h ago	zenogantner	60	19
run	MyMediaLite-matrix-factorization-k-40	217d3h ago	zenogantner	60	19
run	MyMediaLite-matrix-factorization-k-5	217d3h ago	zenogantner	59	19
run	simple-knn-with-tuning-and-shrunk-column	323d18h ago	yorinasub17	59	7
run	whoburg-ALS_K1-r	2y87d ago	whoburg	59	6
run	cberner-KNN-r	2y91d ago	cberner	59	6
run	MyMediaLite-biased-matrix-factorization-k-60	217d3h ago	zenogantner	59	10
run	mjanderson-knn-r	2y88d ago	mjanderson	59	6
run	MyMediaLite-biased-matrix-factorization-k-40	217d3h ago	zenogantner	58	10
run	MyMediaLite-biased-matrix-factorization-k-20	217d18h ago	zenogantner	58	11
run	MyMediaLite-user-average	217d20h ago	zenogantner	58	6
run	mean_user_rating_ruby_2	2y105d ago	jake	58	6
run	lester-shrunk_item_mean-r	2y101d ago	lester	58	15
run	lester-shrunk_item_mean-testSunday	2y91d ago	jjariyas	58	15
run	MyMediaLite-biased-matrix-factorization-k-10	217d3h ago	zenogantner	58	10
run	MyMediaLite-biased-matrix-factorization-k-5	217d3h ago	zenogantner	58	10
run	cberner-KNNImproved-r	2y89d ago	cberner	58	6

1. pagination_page => 0
2. current_sort_col => avg_percentile
3. paginate => true
4. model => Program
5. name => programs
6. limit => 25
7. reverse_sort => true
8. show_footer => true
9. pagination_maxed => false
10. columns => prg_create_runprg_nameprg_created_atprg_userprg_avg_percentileprg_num_runs
11. width => 100%
12. joins =>
13. include => uservresult
14. title => Select a program
15. filters => is_helperfalseprocess_statussuccesstask_typeCollaborativeFiltering

Existing runs on movielens1m (all) 1-25 of 118 < > Filter:

ID	Program	Dataset	Tuned hyper.	User	Updated	Status	Total time	Memory	Error >>
Run #13964	MML-BMF	movielens1m	no	zenogantner	218d15h ago	done	6m24s	423M	0.884
Run #1215	xterm-knnsvd_shrunk_unbias-r	movielens1m	no	xterm	1y122d ago	done	4h16m	1463M	0.887
Run #2344	xterm-knnsvd_shrunk_unbias_rev-r	movielens1m	no	internal	1y122d ago	done	2h51m	1180M	0.887
Run #14853	MyMediaLite-biased-matrix-factorization-k-60	movielens1m	no	internal	208d5h ago	done	1h18m	423M	0.888
Run #14848	MyMediaLite-matrix-factorization-k-20	movielens1m	no	internal	208d15h ago	done	7m41s	423M	0.888
Run #14727	MyMediaLite-matrix-factorization-k-60	movielens1m	no	internal	208d16h ago	done	22m23s	423M	0.889
Run #14755	MyMediaLite-matrix-factorization-k-10	movielens1m	no	internal	208d16h ago	done	6m16s	423M	0.889
Run #14858	MyMediaLite-biased-matrix-factorization-k-10	movielens1m	no	internal	208d14h ago	done	28m9s	423M	0.890
Run #14868	MyMediaLite-biased-matrix-factorization-k-40	movielens1m	no	internal	208d5h ago	done	1h16m	423M	0.891
Run #14741	MyMediaLite-matrix-factorization-k-5	movielens1m	no	internal	208d16h ago	done	4m46s	417M	0.891
Run #14843	MyMediaLite-biased-matrix-factorization-k-20	movielens1m	no	internal	208d15h ago	done	38m40s	423M	0.892
Run #14863	MyMediaLite-biased-matrix-factorization-k-5	movielens1m	no	internal	208d14h ago	done	26m34s	423M	0.893
Run #14769	MyMediaLite-matrix-factorization-k-40	movielens1m	no	internal	208d16h ago	done	12m36s	423M	0.897
Run #14097	MyMediaLite-matrix-factorization-k-5	movielens1m	yes	zenogantner	217d2h ago	done	16m18s	430M	0.899
Run #14121	MyMediaLite-biased-matrix-factorization-k-5	movielens1m	yes	zenogantner	216d20h ago	done	1h14m	431M	0.904
Run #1336	cberner-KNNImproved-r	movielens1m	no	jake	1y122d ago	done	1h29m	833M	0.905
Run #1199	kenghao-matrix_em_k10_v2-r	movielens1m	no	kenghaochang	1y122d ago	done	2h15m	2021M	0.906
Run #919	mjanderson-matrix-factorization-r	movielens1m	no	mjanderson	1y122d ago	done	20m32s	570M	0.909
Run #14093	MyMediaLite-matrix-factorization-k-10	movielens1m	yes	zenogantner	217d2h ago	done	21m45s	430M	0.909
Run #14089	MyMediaLite-matrix-factorization-k-20	movielens1m	yes	zenogantner	217d3h ago	done	32m56s	432M	0.910
Run #1335	lester-mf_rsgd-r	movielens1m	no	jake	1y122d ago	done	34m14s	425M	0.913
Run #14125	MyMediaLite-biased-matrix-factorization-k-10	movielens1m	yes	zenogantner	216d16h ago	done	1h38m	432M	0.914
Run #14117	MyMediaLite-biased-matrix-factorization-k-40	movielens1m	yes	zenogantner	216d18h ago	done	4h46m	431M	0.916
Run #14081	MyMediaLite-matrix-factorization-k-60	movielens1m	yes	zenogantner	217d2h ago	done	1h3m	430M	0.918
Run #1174	kenghao-knn_k50-r	movielens1m	no	kenghaochang	1y122d ago	done	3h10m	667M	0.921

1. pagination_page => 0
2. filter_field => programs.namedatasets.nameruns.idrun_statuses.status
3. current_sort_col => error
4. paginate => true
5. model => Run
6. name => runs
7. limit => 25
8. show_footer => true
9. reverse_sort => false
10. pagination_maxed => false
11. columns => run_idrun_core_programrun_core_datasetrun_hyperrun_userrun_updated_atrun_statusrun_timerun_memoryrun_error
12. width => 100%
13. joins => statuscore_programcore_dataset
14. filters => core_dataset_id335programs.is_helperfalse
15. title => Existing runs on movielens1m

Processing details

• exitCode: 0
• success: true
• test:
  • maxLabelValue: 5.0
  • minLabelValue: 1.0
  • numCols: 3952
  • numExamples: 5000
  • numRows: 5000
  • success: true
  • time: 1
• train:
  • maxLabelValue: 5.0
  • minLabelValue: 1.0
  • numCols: 3952
  • numExamples: 830307
  • numRows: 5000
  • success: true
  • time: 4

Comments:

• 

  Oriol Vinyals (xterm)
  UC Berkeley
  Posted at 11/14/2009

  Uhmm after a lot of tweaking of my R code, I got my thing to run under 5 hours... 0.887 yay!
• 

  Jacob Abernethy (jake)
  UC Berkeley Comp Sci
  Posted at 11/13/2009

  Wow, that's close

  mjanderson got pretty darn close to cberner's lead
• 

  Jacob Abernethy (jake)
  UC Berkeley Comp Sci
  Posted at 11/12/2009

  Mean movie rating

  I would just like to point out how well using the mean movie rating works. How's that for learning :-)