ML project leaderboard

Last update: 2024-09-02

FINAL CHALLENGE RANKING ON HELD-OUT TEST SET

NOTES

Team 67: You submitted the wrong file for your regression task and as such we could not include your team in the final ranking of the regression challenge task.

Team 15 & 17: you wrongly named your test private (ie. Dataset_test_private) for either one task or both, however, we renamed the files for you and included them in the final ranking.

Team 78: you submitted 3 different files, we considered your file test_private_clf for the classification task. However, the other two files were wrongly named (i.e. test_private_rf_pred and test_private_svm_pred) and we did not include them in the final ranking. This is because we did not map which file belongs to which task.

Team 31, 55, 67, & 69: you submitted different files including the test public as such we considered only the test private data and included it in the final ranking.

Team 53: you submitted a test public file for both of your challenge tasks as such we could not include your team in the final ranking.

Regression Results

Team ID	RMSE	MAE
22	10750.42	4259.97
79	10823.07	4447.46
47	10835.94	4019.82
49	10844.21	4823.37
31	10855.19	4496.70
69	10897.63	4760.54
10	10912.42	4568.69
7	10927.34	4301.70
45	10934.97	4481.24
6	10956.54	4055.73
5	10959.20	4264.50
29	10964.85	4648.37
15	11054.29	4398.68
56	11063.53	4892.15
34	11063.53	4892.15
55	11093.65	4795.07
54	11097.50	4495.51
37	11102.71	4458.19
3	11188.25	4222.22
9	11248.90	4113.01
18	11448.82	3905.06
20	11620.12	5706.98
75	11651.87	4244.88
48	11722.97	5210.71
52	12960.42	6266.51
17	13674.82	5054.49
8	27283.65	15445.78

Classification Results

NOTES:

Team 62: You stored classifier predictions wrong. I get an error when loading your classification model file. ValueError: Mix of label input types (string and number)

Last update: 2024-08-23

Regression Results

Team ID	F1 Score
47	0.7886
22	0.7858
6	0.7853
18	0.7842
15	0.7837
79	0.7787
10	0.7772
55	0.7767
54	0.7764
45	0.7764
49	0.7753
31	0.7746
8	0.7742
78	0.7675
9	0.7671
3	0.7669
48	0.7663
29	0.7656
37	0.7644
69	0.7622
17	0.7604
34	0.7563
56	0.7470
67	0.7429
75	0.7296
20	0.7231
5	0.6494
7	0.6070
52	0.4368

Team ID	RMSE	MAE
47	10704.96	3698.14
22	10757.46	4028.12
6	10765.29	3856.85
7	10790.50	4058.01
31	10811.90	4231.08
37	10817.55	4236.48
15	10872.28	4218.28
79	10937.55	4248.33
49	10968.83	4492.17
10	10984.55	4398.86
9	10995.28	3813.87
5	11004.64	4144.42
11	11029.10	4496.07
69	11048.78	4509.58
3	11120.12	3942.35
56	11125.52	4681.96
14	11125.52	4681.96
34	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
29	11138.66	4448.80
78	11178.52	4049.75
23	11196.95	4556.35
70	11220.98	4603.41
55	11333.19	4542.09
18	11470.73	3532.06
75	11682.07	4221.55
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
67	12481.26	4009.39
52	12943.92	5925.53
17	13510.41	4550.89
62	13792.69	4768.73
26	13795.50	4773.46
45	13795.68	4773.56
20	14350.60	7059.26
54	15363.41	7086.39
8	21079690.14	15312283.36
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
6	0.7803
7	0.7770
47	0.7745
18	0.7742
22	0.7729
31	0.7722
79	0.7722
10	0.7714
45	0.7709
54	0.7698
8	0.7679
15	0.7656
11	0.7622
3	0.7621
23	0.7613
29	0.7612
9	0.7606
49	0.7593
69	0.7593
48	0.7576
78	0.7559
37	0.7559
34	0.7430
14	0.7430
82	0.7403
56	0.7403
70	0.7372
53	0.7354
75	0.7236
5	0.6945
20	0.6324
25	0.5481
26	0.5237
17	0.5115
52	0.4423
67	0.3799

####################old#####################

NOTES:

Team 62: You stored classifier predictions wrong. I get an error when loading your classification model file. ValueError: Mix of label input types (string and number)

Last update: 2024-08-23

Regression Results

Team ID	RMSE	MAE
47	10704.96	3698.14
22	10757.46	4028.12
6	10765.29	3856.85
7	10790.50	4058.01
31	10811.90	4231.08
45	10814.31	4211.46
37	10817.55	4236.48
15	10872.28	4218.28
79	10937.55	4248.33
49	10968.83	4492.17
10	10984.55	4398.86
9	10995.28	3813.87
5	11004.64	4144.42
11	11029.10	4496.07
69	11048.78	4509.58
3	11120.12	3942.35
56	11125.52	4681.96
14	11125.52	4681.96
34	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
29	11138.66	4448.80
78	11178.52	4049.75
23	11196.95	4556.35
70	11220.98	4603.41
55	11333.19	4542.09
18	11470.73	3532.06
75	11682.07	4221.55
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
67	12481.26	4009.39
52	12943.92	5925.53
17	13510.41	4550.89
62	13792.69	4768.73
26	13795.50	4773.46
20	14350.60	7059.26
54	15363.41	7086.39
8	21079690.14	15312283.36
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
6	0.7803
15	0.7784
7	0.7770
18	0.7742
22	0.7729
31	0.7722
10	0.7714
45	0.7709
47	0.7699
54	0.7698
79	0.7682
11	0.7622
3	0.7621
23	0.7613
29	0.7612
9	0.7606
49	0.7593
69	0.7593
48	0.7576
78	0.7559
37	0.7559
34	0.7430
14	0.7430
82	0.7403
56	0.7403
70	0.7372
53	0.7354
75	0.7236
8	0.6974
5	0.6945
20	0.6324
25	0.5481
26	0.5237
17	0.5115
52	0.4423
67	0.3799

####################old#####################

NOTES:

Team 62: You stored classifier predictions wrong. I get an error when loading your classification model file. ValueError: Mix of label input types (string and number)

Last update: 2024-08-23

Regression Results

Team ID	RMSE	MAE
47	10704.96	3698.14
22	10757.46	4028.12
6	10765.29	3856.85
31	10811.90	4231.08
7	10812.95	4013.16
45	10814.31	4211.46
37	10817.55	4236.48
79	10937.55	4248.33
49	10968.83	4492.17
10	10984.55	4398.86
9	10995.28	3813.87
5	11004.64	4144.42
11	11029.10	4496.07
69	11048.78	4509.58
3	11120.12	3942.35
56	11125.52	4681.96
14	11125.52	4681.96
34	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
78	11178.52	4049.75
23	11196.95	4556.35
70	11220.98	4603.41
55	11333.19	4542.09
18	11470.73	3532.06
75	11682.07	4221.55
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
67	12481.26	4009.39
52	12943.92	5925.53
17	13510.41	4550.89
62	13792.69	4768.73
26	13795.50	4773.46
20	14350.60	7059.26
15	14852.54	7220.95
54	15363.41	7086.39
8	21079690.14	15312283.36
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
6	0.7803
15	0.7784
18	0.7742
22	0.7729
31	0.7722
10	0.7714
45	0.7709
47	0.7702
54	0.7698
79	0.7682
8	0.7679
7	0.7677
11	0.7622
3	0.7621
23	0.7613
9	0.7606
49	0.7593
69	0.7593
48	0.7576
78	0.7559
37	0.7559
34	0.7430
14	0.7430
82	0.7403
56	0.7403
70	0.7372
53	0.7354
75	0.7236
5	0.6945
20	0.6324
25	0.5481
26	0.5237
17	0.5115
52	0.4423
67	0.3799

####################old#####################

NOTES:

Team 62: You stored classifier predictions wrong. I get an error when loading your classification model file. ValueError: Mix of label input types (string and number)

Last update: 2024-08-22

Regression Results

Team ID	RMSE	MAE
47	10704.96	3698.14
22	10757.46	4028.12
6	10765.29	3856.85
31	10811.90	4231.08
7	10812.95	4013.16
45	10814.31	4211.46
37	10817.55	4236.48
15	10875.12	4290.82
79	10937.55	4248.33
49	10968.83	4492.17
10	10984.55	4398.86
9	10995.28	3813.87
11	11029.10	4496.07
69	11048.78	4509.58
3	11120.12	3942.35
56	11125.52	4681.96
14	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
78	11178.52	4049.75
23	11196.95	4556.35
8	11219.47	3462.44
70	11220.98	4603.41
55	11333.19	4542.09
18	11470.73	3532.06
54	11483.12	4611.74
75	11682.07	4221.55
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
52	12943.92	5925.53
67	13174.84	4241.17
17	13510.41	4550.89
62	13792.69	4768.73
26	13795.50	4773.46
20	14350.60	7059.26
5	20292.76	17136.97
34	50600396.13	36877924.16
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
15	0.7784
6	0.7780
47	0.7764
22	0.7729
31	0.7722
10	0.7714
45	0.7709
79	0.7682
7	0.7679
11	0.7622
3	0.7621
23	0.7613
9	0.7606
49	0.7593
69	0.7593
8	0.7590
18	0.7583
48	0.7576
78	0.7559
37	0.7559
67	0.7440
34	0.7430
14	0.7430
82	0.7403
56	0.7403
70	0.7372
53	0.7354
54	0.7266
75	0.7236
20	0.6324
25	0.5481
26	0.5237
17	0.5115
52	0.4423
5	0.2725

####################old#####################

NOTES:

Team 62: You stored classifier predictions wrong. I get an error when loading your classification model file. ValueError: Mix of label input types (string and number)

Last update: 2024-08-21

Regression Results

Team ID	RMSE	MAE
47	10704.96	3698.14
6	10725.25	3895.86
22	10757.46	4028.12
31	10811.90	4231.08
45	10814.31	4211.46
37	10817.55	4236.48
7	10843.01	4166.75
15	10875.12	4290.82
79	10937.55	4248.33
10	10984.55	4398.86
9	10995.28	3813.87
11	11029.10	4496.07
69	11048.78	4509.58
56	11125.52	4681.96
14	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
3	11142.60	3910.67
34	11155.95	4619.75
78	11178.52	4049.75
23	11196.95	4556.35
8	11219.47	3462.44
70	11220.98	4603.41
55	11333.19	4542.09
18	11470.73	3532.06
54	11483.12	4611.74
75	11682.07	4221.55
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
52	12943.92	5925.53
67	13174.84	4241.17
17	13510.41	4550.89
62	13792.69	4768.73
5	13792.77	4768.68
26	13795.50	4773.46
49	13795.60	4773.73
20	14350.60	7059.26
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
15	0.7784
6	0.7770
7	0.7730
22	0.7729
31	0.7722
10	0.7714
47	0.7711
45	0.7709
79	0.7682
11	0.7622
3	0.7620
23	0.7613
9	0.7606
69	0.7593
8	0.7590
48	0.7576
78	0.7559
37	0.7559
18	0.7534
34	0.7440
67	0.7440
14	0.7430
82	0.7403
56	0.7403
70	0.7372
53	0.7354
54	0.7266
75	0.7236
20	0.6324
25	0.5481
26	0.5237
17	0.5115
52	0.4423
5	0.4166
49	0.1417

####################old#####################

NOTES:

Team 49: I get an Error loading submissions/49__test_public__clf_pred.npy: Object arrays cannot be loaded when allow_pickle=False. We will not allow pickling because it potentially allows remote code execution.

Team 62: You stored classifier predictions wrong. I get an error when loading your classification model file. ValueError: Mix of label input types (string and number)

Last update: 2024-08-20

Regression Results

Team ID	RMSE	MAE
47	10704.96	3698.14
22	10757.46	4028.12
6	10782.99	3844.11
31	10811.90	4231.08
45	10814.31	4211.46
7	10843.01	4166.75
15	10875.12	4290.82
79	10937.55	4248.33
10	10984.55	4398.86
9	10995.28	3813.87
11	11029.10	4496.07
69	11048.78	4509.58
56	11125.52	4681.96
14	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
3	11142.60	3910.67
34	11155.95	4619.75
78	11178.52	4049.75
23	11196.95	4556.35
70	11220.98	4603.41
55	11333.19	4542.09
18	11470.73	3532.06
54	11483.12	4611.74
75	11682.07	4221.55
67	12171.46	3971.89
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
52	12943.92	5925.53
17	13510.41	4550.89
62	13792.69	4768.73
5	13792.87	4768.98
26	13795.50	4773.46
20	14350.60	7059.26
49	14959.04	7030.26
8	21079690.14	15312283.36
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
6	0.7741
7	0.7730
31	0.7722
47	0.7716
10	0.7714
45	0.7709
79	0.7682
11	0.7622
3	0.7620
23	0.7613
9	0.7606
69	0.7593
8	0.7590
15	0.7578
48	0.7576
78	0.7559
37	0.7559
34	0.7440
14	0.7430
82	0.7403
56	0.7403
70	0.7372
53	0.7354
54	0.7266
75	0.7236
20	0.6324
67	0.6266
25	0.5481
26	0.5237
17	0.5115
18	0.4601
52	0.4423
5	0.4166
22	0.3830

####################old#####################

Note:

Team 49 - You stored classifier predictions wrong. I get an error when loading your file: "Object arrays cannot be loaded when allow_pickle=False". We will not allow pickling because it potentially allows remote code execution.

Team 62 You stored classifier predictions wrong. I get an error when loading your file: "Object arrays cannot be loaded when allow_pickle=False". I will not allow pickling because it potentially allows remote code execution.

Last update: 2024-08-19

Regression Results

Team ID	RMSE	MAE
47	10704.96	3698.14
22	10788.23	4045.27
6	10793.46	3726.70
31	10811.90	4231.08
45	10814.31	4211.46
7	10843.01	4166.75
15	10875.12	4290.82
79	10937.55	4248.33
10	10984.55	4398.86
9	10995.28	3813.87
37	11003.74	4566.01
11	11029.10	4496.07
69	11048.78	4509.58
56	11125.52	4681.96
14	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
3	11142.60	3910.67
23	11196.95	4556.35
70	11220.98	4603.41
55	11333.19	4542.09
54	11483.12	4611.74
75	11682.07	4221.55
18	12072.27	3710.58
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
67	12643.97	3929.88
17	13510.41	4550.89
62	13792.69	4768.73
5	13792.87	4768.98
26	13795.50	4773.46
20	14350.60	7059.26
52	14835.52	7069.17
49	15034.05	7001.19
8	21079690.14	15312283.36
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
6	0.7803
7	0.7730
22	0.7729
47	0.7720
10	0.7714
45	0.7709
79	0.7682
11	0.7622
3	0.7620
23	0.7613
9	0.7606
69	0.7593
8	0.7590
15	0.7578
48	0.7576
78	0.7559
37	0.7559
14	0.7430
82	0.7403
56	0.7403
70	0.7372
53	0.7354
52	0.7331
54	0.7266
75	0.7236
20	0.6324
25	0.5481
26	0.5237
17	0.5115
67	0.4519
5	0.4166
18	0.1830

Note: Leaderboard entries up until 2024-08-14 showed only the MAE scores. From 2024-08-15 on, also the RMSE is shown, which we use to do the final evaluation (as is written in the project instructions). Entries are sorted by RMSE.

Last update: 2024-08-18, 10:15pm

Regression Results

Team ID	RMSE	MAE
47	10704.96	3698.14
22	10775.82	4057.06
6	10793.46	3726.70
31	10811.90	4231.08
45	10814.31	4211.46
7	10843.01	4166.75
15	10861.47	4306.13
79	10937.55	4248.33
10	10984.55	4398.86
37	11003.74	4566.01
56	11125.52	4681.96
14	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
3	11142.60	3910.67
11	11156.35	3485.27
23	11196.95	4556.35
70	11220.98	4603.41
55	11333.19	4542.09
18	11470.73	3532.06
54	11483.12	4611.74
75	11682.07	4221.55
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
9	12555.29	3803.88
17	13510.41	4550.89
67	13720.07	4684.03
26	13795.50	4773.46
20	14350.60	7059.26
52	14835.52	7069.17
49	15034.05	7001.19
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
6	0.7803
15	0.7784
7	0.7730
10	0.7714
45	0.7709
79	0.7682
22	0.7633
11	0.7622
3	0.7620
47	0.7613
23	0.7613
9	0.7606
48	0.7576
78	0.7559
37	0.7559
67	0.7440
14	0.7430
18	0.7412
56	0.7403
82	0.7403
70	0.7372
53	0.7354
52	0.7331
54	0.7266
75	0.7236
20	0.6324
25	0.5481
26	0.5237
17	0.5115

Notes:

Team 49 - You stored classifier predictions wrong. I get an error when loading your file: "Object arrays cannot be loaded when allow_pickle=False". I will not allow pickling because it potentially allows remote code execution.

##################### old #########################

Last update: 2024-08-18

Regression Results

Team ID	RMSE	MAE
47	10704.96	3698.14
22	10757.46	4028.12
6	10793.46	3726.70
31	10811.90	4231.08
45	10814.31	4211.46
15	10870.28	4227.37
7	10893.62	4198.12
79	10937.55	4248.33
10	10987.12	4277.74
14	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
3	11176.24	3969.00
23	11196.95	4556.35
70	11220.98	4603.41
11	11300.62	3517.52
55	11333.19	4542.09
18	11470.73	3532.06
54	11483.12	4611.74
75	11682.07	4221.55
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
9	12555.29	3803.88
17	13510.41	4550.89
67	13720.07	4684.03
26	13795.50	4773.46
20	14350.60	7059.26
37	14758.01	7326.49
52	14835.52	7069.17
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
6	0.7803
15	0.7784
45	0.7709
10	0.7684
47	0.7655
7	0.7637
79	0.7636
23	0.7613
9	0.7606
48	0.7570
18	0.7495
11	0.7488
3	0.7457
67	0.7440
14	0.7430
78	0.7430
82	0.7403
70	0.7372
53	0.7354
52	0.7331
54	0.7266
75	0.7236
22	0.6881
20	0.6324
25	0.5481
26	0.5237
17	0.5115
37	0.4589

################## old ###################

Last update: 2024-08-17

Regression Results

Team ID	RMSE	MAE
47	10704.96	3698.14
6	10793.46	3726.70
45	10814.31	4211.46
15	10870.28	4227.37
7	10893.62	4198.12
79	10937.55	4248.33
22	10946.00	4268.76
14	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
23	11196.95	4556.35
70	11220.98	4603.41
11	11300.62	3517.52
55	11333.19	4542.09
18	11470.73	3532.06
54	11483.12	4611.74
75	11682.07	4221.55
3	12118.60	3622.18
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
9	12555.29	3803.88
10	12606.63	4334.61
17	13510.41	4550.89
67	13720.07	4684.03
52	13788.21	4761.00
26	13795.50	4773.46
20	14350.60	7059.26
37	14758.01	7326.49
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
6	0.7803
15	0.7730
22	0.7729
47	0.7708
10	0.7684
7	0.7637
23	0.7613
9	0.7606
45	0.7584
48	0.7576
52	0.7512
11	0.7488
3	0.7469
67	0.7440
14	0.7430
78	0.7430
79	0.7429
82	0.7403
70	0.7372
53	0.7354
54	0.7266
75	0.7236
18	0.6496
20	0.6324
25	0.5481
26	0.5237
17	0.5115
37	0.4589

##################### old ####################

Last update: 2024-08-16

Regression Results

Team ID	RMSE	MAE
47	10721.41	3647.50
79	10819.75	4256.00
15	10870.28	4227.37
7	10893.62	4198.12
6	10924.48	3750.09
22	10946.00	4268.76
54	10966.49	4186.78
10	10991.70	4419.38
14	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
23	11196.95	4556.35
70	11220.98	4603.41
11	11300.62	3517.52
55	11333.19	4542.09
75	11682.07	4221.55
18	11892.41	3592.93
3	12118.60	3622.18
16	12251.70	5467.88
25	12312.71	4046.94
82	12375.62	4901.83
9	12555.29	3803.88
52	12949.06	6208.75
48	13509.57	4550.92
17	13510.41	4550.89
67	13720.07	4684.03
45	13795.66	4773.60
20	14350.60	7059.26
37	14758.01	7326.49
68	5808859298265272680448.00	222852054139525136384.00

Classification Results

Team ID	F1 Score
15	0.7785
22	0.7729
6	0.7703
10	0.7680
7	0.7637
23	0.7613
9	0.7606
45	0.7584
47	0.7562
79	0.7560
54	0.7541
11	0.7488
3	0.7469
67	0.7440
14	0.7430
78	0.7430
82	0.7403
70	0.7372
53	0.7354
75	0.7236
18	0.6690
20	0.6324
25	0.5481
17	0.5115
37	0.4589
48	0.4578
52	0.4423

####################### old ########################

Last update: 2024-08-15 - second update of the day

Regression Results

Team ID	RMSE	MAE
15	10883.79	4300.27
79	10890.15	4211.13
6	10924.48	3750.09
22	10946.00	4268.76
14	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
23	11196.95	4556.35
70	11220.98	4603.41
3	11237.23	4203.05
10	11258.34	3998.24
11	11300.62	3517.52
55	11333.19	4542.09
18	11892.41	3592.93
75	11907.73	4284.77
47	12134.08	3628.34
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
9	12555.29	3803.88
52	12949.06	6208.75
17	13510.41	4550.89
67	13720.07	4684.03
45	13795.66	4773.60
20	14350.60	7059.26
37	14758.01	7326.49
7	10342424.08	6742417.42
68	very high	very high

Classification Results

Team ID	F1 Score
15	0.7785
22	0.7729
6	0.7703
10	0.7680
23	0.7613
9	0.7606
45	0.7584
48	0.7576
79	0.7560
11	0.7488
3	0.7469
67	0.7440
14	0.7430
78	0.7430
82	0.7403
70	0.7372
53	0.7354
75	0.6992
20	0.6324
25	0.5481
17	0.5115
52	0.4423
18	0.2805
47	0.1384

Notes:

Team 7 - Error calculating F1 score: "Found input variables with inconsistent numbers of samples: [4791, 15000]"

############### old #########################

Last update: 2024-08-15

Regression Results

Team ID	RMSE	MAE
15	10883.79	4300.27
79	10890.15	4211.13
6	10924.48	3750.09
22	10946.00	4268.76
14	11125.52	4681.96
7	11125.52	4681.96
53	11125.52	4681.96
46	11125.52	4681.96
23	11196.95	4556.35
70	11220.98	4603.41
10	11258.34	3998.24
55	11333.19	4542.09
18	11892.41	3592.93
75	11907.73	4284.77
47	12134.08	3628.34
16	12251.70	5467.88
48	12265.92	5134.39
25	12312.71	4046.94
82	12375.62	4901.83
9	12555.29	3803.88
11	12665.98	3923.76
52	12949.06	6208.75
17	13510.41	4550.89
67	13720.07	4684.03
45	13795.66	4773.60
20	14350.60	7059.26
37	14758.01	7326.49
68	very high...	very high...

Classification Results

Team ID	F1 Score
15	0.7785
22	0.7729
6	0.7703
10	0.7680
23	0.7613
9	0.7606
45	0.7584
48	0.7576
79	0.7560
67	0.7440
14	0.7430
7	0.7430
82	0.7403
70	0.7372
53	0.7354
11	0.7018
75	0.6992
20	0.6324
25	0.5481
17	0.5115
52	0.4423
18	0.3113
47	0.1384

####################### old ######################

Last update: 2024-08-14

Regression Results

Team ID	Score
18	3532.061644
9	3803.884539
11	3923.760080
10	3998.242595
25	4046.940581
79	4211.127396
75	4284.768454
15	4300.265746
22	4331.678814
55	4542.092888
17	4550.890731
23	4556.352123
70	4603.407788
14	4681.957287
7	4681.957287
46	4681.957287
67	4684.032732
45	4773.603267
6	4773.613442
82	4901.828521
48	5134.394765
16	5467.880972
52	6208.745518
20	7059.261998
37	7326.493843
68	222852054139525136384.000000

Classification Results

Team ID	F1 Score
15	0.778476
22	0.771810
10	0.768007
23	0.761328
45	0.758356
48	0.757564
9	0.756390
67	0.743983
14	0.743043
7	0.743043
82	0.740350
70	0.737200
11	0.701841
75	0.699199
20	0.632380
25	0.548127
17	0.511544
18	0.456495
52	0.442258

####################old#####################

Last update: 2024-08-12

Regression Results

Team ID	Score
18	3532.061644
9	3803.884539
11	3923.760080
25	4046.940581
22	4331.678814
10	4357.885510
55	4542.092888
17	4550.890731
15	4557.613887
70	4603.407788
23	4661.466649
14	4681.957287
7	4681.957287
46	4681.957287
67	4684.032732
45	4773.603267
6	4773.613442
82	4901.828521
48	5134.394765
52	5920.364723
20	7059.261998
16	898801418424.161987
68	222852054139525136384.000000

Classification Results

Team ID	F1 Score
22	0.771810
10	0.768007
23	0.761328
45	0.758356
9	0.756390
52	0.756353
67	0.743983
14	0.743043
7	0.743043
82	0.740350
70	0.737200
20	0.632380
25	0.548127
17	0.511544
18	0.266333

Notes:

Team 11 - You stored classifier predictions wrong. I get an error when loading your file: "Object arrays cannot be loaded when allow_pickle=False". I will not allow pickling because it potentially allows remote code execution.

####################old#####################

Last update: 2024-08-08

Regression Results

Team ID	Score
18	3558.139915
6	3737.913734
9	3803.884539
11	3923.760080
25	4046.940581
22	4331.678814
10	4357.885510
55	4542.092888
17	4550.890731
15	4557.613887
70	4603.407788
23	4661.466649
14	4681.957287
7	4681.957287
46	4681.957287
67	4684.032732
45	4773.603267
82	4901.828521
52	5920.364723
20	7059.261998
16	898801418424.161987
68	222852054139525136384.000000

Classification Results

Team ID	F1 Score
6	0.777258
22	0.771810
10	0.768007
18	0.763880
23	0.761328
45	0.758356
52	0.756353
67	0.743983
14	0.743043
7	0.743043
82	0.740350
70	0.737200
20	0.632380
25	0.548127
17	0.511544

################## Old ###################

Last update: 2024-08-05

Regression Results

Team ID	Score
6	3737.913734
9	3803.884539
11	3923.760080
25	4046.940581
22	4331.678814
10	4357.885510
55	4542.092888
17	4550.890731
15	4554.635299
70	4603.407788
14	4681.957287
7	4681.957287
46	4681.957287
67	4684.032732
45	4773.603267
82	4901.828521
23	5080.487465
18	5101.583436
20	7828.562266
16	898801418424.161987

Classification Results

Team ID	F1 Score
6	0.782399
22	0.771810
10	0.768007
23	0.765682
18	0.762959
45	0.758356
15	0.745940
67	0.743983
14	0.743043
7	0.743043
82	0.740350
70	0.737200
25	0.548127
17	0.511544

Notes:

#################### old ####################

Last update: 2024-07-22

Regression Results

Team ID	Score
11	3928.125762
6	4004.960623
25	4046.940581
22	4331.678814
10	4357.885510
18	4411.313244
55	4542.092888
15	4554.635299
70	4603.407788
14	4681.957287
7	4681.957287
46	4681.957287
67	4684.032732
17	4760.035153
45	4773.603267
82	4901.828521
23	5080.487465
20	7828.562266
16	898801418424.161987

Classification Results

Team ID	F1 Score
6	0.782399
22	0.771810
10	0.768007
23	0.765682
18	0.764521
45	0.758356
15	0.745940
67	0.743983
14	0.743043
7	0.743043
82	0.740350
70	0.737200
17	0.730625
25	0.548127

Notes:

Teams 22,25,55,82 and 67: Please do not put your submission files into an extra folder in the zip.

############# old ####################

Last update: 2024-07-16

Regression Results

Team ID	Score
25	4046.940581
6	4053.648429
22	4331.678814
10	4357.885510
18	4411.313244
15	4554.635299
70	4603.407788
14	4681.957287
7	4681.957287
46	4681.957287
45	4773.603267
11	4894.274683
82	4901.828521
23	5080.487465
20	5468.731419
37	7324.104578

Classification Results

Team ID	F1 Score
22	0.771810
6	0.769445
10	0.768007
23	0.765682
18	0.764521
55	0.761424
45	0.758356
15	0.745940
14	0.743043
7	0.743043
20	0.742078
82	0.740350
70	0.737200
25	0.548127

Notes

Team 37 - You stored classifier predictions wrong. I get an error when loading your file: "Object arrays cannot be loaded when allow_pickle=False". I will not allow pickling because it potentially allows remote code execution.

#########################old###################

Last update: 2024-07-08

Regression Results

Team ID	Score
6	3965.016228
25	4240.207851
22	4331.678814
10	4357.885510
18	4411.313244
70	4603.407788
15	4624.411712
14	4681.957287
7	4681.957287
46	4681.957287
45	4773.603267
82	4901.828521
23	5080.487465
20	5281.968461

Classification Results

Team ID	F1 Score
22	0.771810
10	0.768007
23	0.765682
6	0.764800
18	0.764521
45	0.758356
14	0.743043
7	0.743043
15	0.740350
82	0.740350
20	0.739889
70	0.737200
25	0.716781

Notes:

Team 37: You stored classifier predictions wrong. I get an Error loading your file: "Object arrays cannot be loaded when allow_pickle=False". I will not allow pickling because it potentially allows remote code execution.

#####################old#######################

Last update: 2024-07-02

Regression Results

Team ID	Score
6	4195.140712
25	4240.207851
22	4331.678814
10	4357.885510
18	4411.313244
15	4624.411712
14	4681.957287
82	4681.957287
46	4681.957287
45	4773.603267
23	5080.487465
20	5281.968461

Classification Results

Team ID	F1 Score
22	0.771810
10	0.768007
23	0.765682
6	0.765552
18	0.764521
45	0.758356
14	0.743043
82	0.743043
15	0.740350
20	0.739889
25	0.716781

#####################old#######################

Regression Results

Team ID	Score
6	3965.016228
25	4240.207851
15	4624.411712
14	4681.957287
46	4681.957287
45	4773.603267
23	5080.487465
20	6434.402668

Classification Results

Team ID	F1 Score
10	0.768007
23	0.765682
45	0.758356
14	0.743043
15	0.740350
20	0.739889
25	0.716781

############################## OLD ##############################

Last update: 2024-06-17

Regression Results

Team ID	Score
6	3965.016228
25	4046.940581
23	4609.761559
15	4669.311288
14	4681.957287
46	4681.957287
45	4773.603267
20	6434.402668

Classification Results

Team ID	F1 Score
45	0.758356
14	0.743043
15	0.740350
20	0.739889
23	0.701411
25	0.641015

Errors/Notes:

Team 10: You stored classifier predictions wrong. I get an "Error loading 10__test_public__clf_pred.npy: Object arrays cannot be loaded when allow_pickle=False". I will not allow pickling because it potentially allows remote code execution.

############################## OLD ##############################

Old results from: 2024-06-10

Regression Results

Team ID	Score
6	3965.016228
23	4609.761559
14	4681.957287
46	4681.957287
45	4773.603267
20	6434.402668

Classification Results

Team ID	F1 Score
6	0.768055
45	0.758356
14	0.743043
20	0.739889
23	0.701411

Errors/Notes:

Team 6, the file containing your classification predictions had the wrong filename.

Machine Learning