Difference between revisions of "2008:Audio Music Mood Classification Results"
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==Introduction== | ==Introduction== | ||
| − | These are the results for the 2008 running of the Audio Music Mood Classification task. For background information about this task set please refer to the [[Audio Music Mood Classification]] page. | + | These are the results for the 2008 running of the Audio Music Mood Classification task. For background information about this task set please refer to the [[2008:Audio Music Mood Classification]] page. |
===General Legend=== | ===General Legend=== | ||
====Team ID==== | ====Team ID==== | ||
| − | '''GP1''' = [https://www.music-ir.org/mirex/2008/ | + | '''GP1''' = [https://www.music-ir.org/mirex/abstracts/2008/Peeters_2008_ISMIR_MIREX.pdf G. Peeters]<br /> |
| − | '''GT1''' = [https://www.music-ir.org/mirex/2008/ | + | '''GT1''' = [https://www.music-ir.org/mirex/abstracts/2008/mirex2007.pdf G. Tzanetakis]<br /> |
| − | '''GT2''' = [https://www.music-ir.org/mirex/2008/ | + | '''GT2''' = [https://www.music-ir.org/mirex/abstracts/2008/mirex2007.pdf G. Tzanetakis]<br /> |
| − | '''GT3''' = [https://www.music-ir.org/mirex/2008/ | + | '''GT3''' = [https://www.music-ir.org/mirex/abstracts/2008/mirex2007.pdf G. Tzanetakis]<br /> |
| − | '''HW''' = [https://www.music-ir.org/mirex/2008 | + | '''HW''' = [https://www.music-ir.org/mirex/abstracts/2008/.pdf H. Wang]<br /> |
| − | '''KL''' = [https://www.music-ir.org/mirex/2008 | + | '''KL''' = [https://www.music-ir.org/mirex/abstracts/2008/.pdf K. Lee]<br /> |
| − | '''LRPPI1''' = [https://www.music-ir.org/mirex/2008/ | + | '''LRPPI1''' = [https://www.music-ir.org/mirex/abstracts/2008/abstract_mirex08_class.pdf T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 1]<br /> |
| − | '''LRPPI2''' = [https://www.music-ir.org/mirex/2008/ | + | '''LRPPI2''' = [https://www.music-ir.org/mirex/abstracts/2008/abstract_mirex08_class.pdf T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 2]<br /> |
| − | '''LRPPI3''' = [https://www.music-ir.org/mirex/2008/ | + | '''LRPPI3''' = [https://www.music-ir.org/mirex/abstracts/2008/abstract_mirex08_class.pdf T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 3]<br /> |
| − | '''LRPPI4''' = [https://www.music-ir.org/mirex/2008/ | + | '''LRPPI4''' = [https://www.music-ir.org/mirex/abstracts/2008/abstract_mirex08_class.pdf T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 4]<br /> |
| − | '''ME1''' = [https://www.music-ir.org/mirex/2008/ | + | '''ME1''' = [https://www.music-ir.org/mirex/abstracts/2008/AA_AG_AT_MM_CC_mandel.pdf M. I. Mandel, D. P. W. Ellis 1]<br /> |
| − | '''ME2''' = [https://www.music-ir.org/mirex/2008/ | + | '''ME2''' = [https://www.music-ir.org/mirex/abstracts/2008/AA_AG_AT_MM_CC_mandel.pdf M. I. Mandel, D. P. W. Ellis 2]<br /> |
| − | '''ME3''' = [https://www.music-ir.org/mirex/2008/ | + | '''ME3''' = [https://www.music-ir.org/mirex/abstracts/2008/AA_AG_AT_MM_CC_mandel.pdf M. I. Mandel, D. P. W. Ellis 3]<br /> |
==Overall Summary Results== | ==Overall Summary Results== | ||
===MIREX 2008 Audio Mood Classification Summary Results - Raw Classification Accuracy Averaged Over Three Train/Test Folds=== | ===MIREX 2008 Audio Mood Classification Summary Results - Raw Classification Accuracy Averaged Over Three Train/Test Folds=== | ||
| − | <csv>mood/audiomood.avg.results.csv</csv> | + | <csv>2008/mood/audiomood.avg.results.csv</csv> |
=====Accuracy Across Folds===== | =====Accuracy Across Folds===== | ||
| − | <csv>mood/audiomood.results.fold.csv</csv> | + | <csv>2008/mood/audiomood.results.fold.csv</csv> |
=====Accuracy Across Categories===== | =====Accuracy Across Categories===== | ||
| − | <csv>mood/audiomood.results.class.csv</csv> | + | <csv>2008/mood/audiomood.results.class.csv</csv> |
===MIREX 2008 Audio Artist Classification Evaluation Logs and Confusion Matrices=== | ===MIREX 2008 Audio Artist Classification Evaluation Logs and Confusion Matrices=== | ||
| Line 35: | Line 35: | ||
====MIREX 2008 Audio Mood Classification Run Times==== | ====MIREX 2008 Audio Mood Classification Run Times==== | ||
| − | <csv>mood.runtime.csv</csv> | + | <csv>2008/mood.runtime.csv</csv> |
====CSV Files Without Rounding==== | ====CSV Files Without Rounding==== | ||
| − | [https://www.music-ir.org/mirex/2008 | + | [https://www.music-ir.org/mirex/results/2008/mood/audiomood_results_fold.csv audiomood_results_fold.csv]<br /> |
| − | [https://www.music-ir.org/mirex/2008 | + | [https://www.music-ir.org/mirex/results/2008/mood/audiomood_results_class.csv audiomood_results_class.csv]<br /> |
====Results By Algorithm==== | ====Results By Algorithm==== | ||
(.tar.gz) <br /> | (.tar.gz) <br /> | ||
| − | '''GP1''' = [https://www.music-ir.org/mirex/2008 | + | '''GP1''' = [https://www.music-ir.org/mirex/results/2008/mood/GP1.tar.gz G. Peeters]<br /> |
| − | '''GT1''' = [https://www.music-ir.org/mirex/2008 | + | '''GT1''' = [https://www.music-ir.org/mirex/results/2008/mood/GT1.tar.gz G. Tzanetakis]<br /> |
| − | '''GT2''' = [https://www.music-ir.org/mirex/2008 | + | '''GT2''' = [https://www.music-ir.org/mirex/results/2008/mood/GT2.tar.gz G. Tzanetakis]<br /> |
| − | '''GT3''' = [https://www.music-ir.org/mirex/2008 | + | '''GT3''' = [https://www.music-ir.org/mirex/results/2008/mood/GT3.tar.gz G. Tzanetakis]<br /> |
| − | '''HW''' = [https://www.music-ir.org/mirex/2008 | + | '''HW''' = [https://www.music-ir.org/mirex/results/2008/mood/HW.tar.gz G. H. Wang]<br /> |
| − | '''KL''' = [https://www.music-ir.org/mirex/2008 | + | '''KL''' = [https://www.music-ir.org/mirex/results/2008/mood/KL.tar.gz K. Lee]<br /> |
| − | '''LRPPI1''' = [https://www.music-ir.org/mirex/2008 | + | '''LRPPI1''' = [https://www.music-ir.org/mirex/results/2008/mood/LRPPI1.tar.gz T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 1]<br /> |
| − | '''LRPPI2''' = [https://www.music-ir.org/mirex/2008 | + | '''LRPPI2''' = [https://www.music-ir.org/mirex/results/2008/mood/LRPPI2.tar.gz T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 2]<br /> |
| − | '''LRPPI3''' = [https://www.music-ir.org/mirex/2008 | + | '''LRPPI3''' = [https://www.music-ir.org/mirex/results/2008/mood/LRPPI3.tar.gz T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 3]<br /> |
| − | '''LRPPI4''' = [https://www.music-ir.org/mirex/2008 | + | '''LRPPI4''' = [https://www.music-ir.org/mirex/results/2008/mood/LRPPI4.tar.gz T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 4]<br /> |
| − | '''ME1''' = [https://www.music-ir.org/mirex/2008 | + | '''ME1''' = [https://www.music-ir.org/mirex/results/2008/mood/ME1.tar.gz I. M. Mandel, D. P. W. Ellis 1]<br /> |
| − | '''ME2''' = [https://www.music-ir.org/mirex/2008 | + | '''ME2''' = [https://www.music-ir.org/mirex/results/2008/mood/ME2.tar.gz I. M. Mandel, D. P. W. Ellis 2]<br /> |
| − | '''ME3''' = [https://www.music-ir.org/mirex/2008 | + | '''ME3''' = [https://www.music-ir.org/mirex/results/2008/mood/ME3.tar.gz I. M. Mandel, D. P. W. Ellis 3]<br /> |
===Friedman's Test for Significant Differences=== | ===Friedman's Test for Significant Differences=== | ||
| Line 63: | Line 63: | ||
=====Friedman's Anova Table===== | =====Friedman's Anova Table===== | ||
| − | <csv>mood/perClassAccuracy.friedman.csv</csv> | + | <csv>2008/mood/perClassAccuracy.friedman.csv</csv> |
=====Tukey-Kramer HSD Multi-Comparison===== | =====Tukey-Kramer HSD Multi-Comparison===== | ||
| Line 69: | Line 69: | ||
Command: [c, m, h, gnames] = multicompare(stats, 'ctype', 'tukey-kramer', 'estimate', 'friedman', 'alpha', 0.05); | Command: [c, m, h, gnames] = multicompare(stats, 'ctype', 'tukey-kramer', 'estimate', 'friedman', 'alpha', 0.05); | ||
| − | <csv>mood/perClassAccuracy.friedman.detail.csv</csv> | + | <csv>2008/mood/perClassAccuracy.friedman.detail.csv</csv> |
| − | [[Image: | + | [[Image:2008_mood.perclassaccuracy.friedman.tukeykramerhsd.png]] |
====Folds vs. Systems==== | ====Folds vs. Systems==== | ||
| Line 78: | Line 78: | ||
=====Friedman's Anova Table===== | =====Friedman's Anova Table===== | ||
| − | <csv>mood/perFoldAccuracy.friedman.csv</csv> | + | <csv>2008/mood/perFoldAccuracy.friedman.csv</csv> |
=====Tukey-Kramer HSD Multi-Comparison===== | =====Tukey-Kramer HSD Multi-Comparison===== | ||
| Line 84: | Line 84: | ||
Command: [c, m, h, gnames] = multicompare(stats, 'ctype', 'tukey-kramer', 'estimate', 'friedman', 'alpha', 0.05); | Command: [c, m, h, gnames] = multicompare(stats, 'ctype', 'tukey-kramer', 'estimate', 'friedman', 'alpha', 0.05); | ||
| − | <csv>mood/perFoldAccuracy.friedman.detail.csv</csv> | + | <csv>2008/mood/perFoldAccuracy.friedman.detail.csv</csv> |
| − | [[Image: | + | [[Image:2008_mood.perfoldaccuracy.friedman.tukeykramerhsd.png]] |
[[Category: Results]] | [[Category: Results]] | ||
Latest revision as of 16:20, 23 July 2010
Contents
Introduction
These are the results for the 2008 running of the Audio Music Mood Classification task. For background information about this task set please refer to the 2008:Audio Music Mood Classification page.
General Legend
Team ID
GP1 = G. Peeters
GT1 = G. Tzanetakis
GT2 = G. Tzanetakis
GT3 = G. Tzanetakis
HW = H. Wang
KL = K. Lee
LRPPI1 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 1
LRPPI2 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 2
LRPPI3 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 3
LRPPI4 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 4
ME1 = M. I. Mandel, D. P. W. Ellis 1
ME2 = M. I. Mandel, D. P. W. Ellis 2
ME3 = M. I. Mandel, D. P. W. Ellis 3
Overall Summary Results
MIREX 2008 Audio Mood Classification Summary Results - Raw Classification Accuracy Averaged Over Three Train/Test Folds
| Participant | Average Classifcation Accuracy |
|---|---|
| GP1 | 63.67% |
| GT1 | 55.00% |
| GT2 | 52.50% |
| GT3 | 58.20% |
| HW | 30.33% |
| KL | 49.83% |
| LRPPI1 | 56.00% |
| LRPPI2 | 55.50% |
| LRPPI3 | 54.50% |
| LRPPI4 | 55.50% |
| ME1 | 50.33% |
| ME2 | 50.00% |
| ME3 | 49.67% |
Accuracy Across Folds
| Classification fold | GP1 | GT1 | GT2 | GT3 | HW | KL | LRPPI1 | LRPPI2 | LRPPI3 | LRPPI4 | ME1 | ME2 | ME3 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.715 | 0.630 | 0.565 | 0.679 | 0.365 | 0.515 | 0.660 | 0.610 | 0.635 | 0.625 | 0.545 | 0.540 | 0.535 |
| 1 | 0.610 | 0.550 | 0.535 | 0.549 | 0.315 | 0.520 | 0.480 | 0.505 | 0.485 | 0.510 | 0.510 | 0.505 | 0.510 |
| 2 | 0.585 | 0.470 | 0.475 | 0.518 | 0.230 | 0.460 | 0.540 | 0.550 | 0.515 | 0.530 | 0.455 | 0.455 | 0.445 |
Accuracy Across Categories
| Class | GP1 | GT1 | GT2 | GT3 | HW | KL | LRPPI1 | LRPPI2 | LRPPI3 | LRPPI4 | ME1 | ME2 | ME3 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 0.517 | 0.542 | 0.633 | 0.408 | 0.175 | 0.250 | 0.467 | 0.492 | 0.533 | 0.517 | 0.450 | 0.450 | 0.450 |
| 2 | 0.517 | 0.550 | 0.350 | 0.492 | 0.100 | 0.367 | 0.508 | 0.467 | 0.475 | 0.450 | 0.358 | 0.350 | 0.350 |
| 3 | 0.833 | 0.775 | 0.683 | 0.758 | 0.817 | 0.842 | 0.775 | 0.792 | 0.750 | 0.783 | 0.550 | 0.550 | 0.550 |
| 4 | 0.500 | 0.417 | 0.467 | 0.492 | 0.100 | 0.250 | 0.425 | 0.417 | 0.408 | 0.400 | 0.492 | 0.483 | 0.475 |
| 5 | 0.817 | 0.467 | 0.492 | 0.798 | 0.325 | 0.783 | 0.625 | 0.608 | 0.558 | 0.625 | 0.667 | 0.667 | 0.658 |
MIREX 2008 Audio Artist Classification Evaluation Logs and Confusion Matrices
MIREX 2008 Audio Mood Classification Run Times
| Participant | Runtime (hh:mm) / Fold |
|---|---|
| GP1 | Feat Ex: 01:01 Train/Classify: 00:02 |
| GT1 | Feat Ex/Train/Classify: 00:03 |
| GT2 | Feat Ex/Train/Classify: 00:07 |
| GT3 | Feat Ex: 00:01 Train/Classify: 00:00 (1 sec) |
| HW | Feat Ex/Train/Classify: 09:33 |
| KL | Feat Ex/Train/Classify: 00:09 |
| LRPPI1 | Feat Ex: 02:48 Train/Classify: 00:00 (11 sec) |
| LRPPI2 | Feat Ex: 02:48 Train/Classify: 00:00 (29 sec) |
| LRPPI3 | Feat Ex: 02:48 Train/Classify: 00:00 (30 sec) |
| LRPPI4 | Feat Ex: 02:48 Train/Classify: 00:00 (46 sec) |
| ME1 | Feat Ex: 0:20 Train/Classify: 00:00 (2 sec) |
| ME2 | Feat Ex: 0:20 Train/Classify: 00:00 (2 sec) |
| ME3 | Feat Ex: 0:20 Train/Classify: 00:00 (2 sec) |
CSV Files Without Rounding
audiomood_results_fold.csv
audiomood_results_class.csv
Results By Algorithm
(.tar.gz)
GP1 = G. Peeters
GT1 = G. Tzanetakis
GT2 = G. Tzanetakis
GT3 = G. Tzanetakis
HW = G. H. Wang
KL = K. Lee
LRPPI1 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 1
LRPPI2 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 2
LRPPI3 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 3
LRPPI4 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de León, J. M. Iñesta 4
ME1 = I. M. Mandel, D. P. W. Ellis 1
ME2 = I. M. Mandel, D. P. W. Ellis 2
ME3 = I. M. Mandel, D. P. W. Ellis 3
Friedman's Test for Significant Differences
Classes vs. Systems
The Friedman test was run in MATLAB against the average accuracy for each class.
Friedman's Anova Table
| Source | SS | df | MS | Chi-sq | Prob>Chi-sq |
|---|---|---|---|---|---|
| Columns | 157.2 | 10 | 15.72 | 14.34 | 0.1579 |
| Error | 390.8 | 40 | 9.77 | ||
| Total | 548 | 54 |
Tukey-Kramer HSD Multi-Comparison
The Tukey-Kramer HSD multi-comparison data below was generated using the following MATLAB instruction. Command: [c, m, h, gnames] = multicompare(stats, 'ctype', 'tukey-kramer', 'estimate', 'friedman', 'alpha', 0.05);
| TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
|---|---|---|---|---|---|
| GP1 | GT1 | -3.6392 | 3.1000 | 9.8392 | FALSE |
| GP1 | GT2 | -3.3392 | 3.4000 | 10.1392 | FALSE |
| GP1 | GT3 | -2.4392 | 4.3000 | 11.0392 | FALSE |
| GP1 | HW | -2.8392 | 3.9000 | 10.6392 | FALSE |
| GP1 | KL | -3.5392 | 3.2000 | 9.9392 | FALSE |
| GP1 | LRPPI1 | -2.1392 | 4.6000 | 11.3392 | FALSE |
| GP1 | LRPPI2 | -1.9392 | 4.8000 | 11.5392 | FALSE |
| GP1 | LRPPI3 | -1.8392 | 4.9000 | 11.6392 | FALSE |
| GP1 | LRPPI4 | -2.3392 | 4.4000 | 11.1392 | FALSE |
| GP1 | ME1 | 0.6608 | 7.4000 | 14.1392 | TRUE |
| GT1 | GT2 | -6.4392 | 0.3000 | 7.0392 | FALSE |
| GT1 | GT3 | -5.5392 | 1.2000 | 7.9392 | FALSE |
| GT1 | HW | -5.9392 | 0.8000 | 7.5392 | FALSE |
| GT1 | KL | -6.6392 | 0.1000 | 6.8392 | FALSE |
| GT1 | LRPPI1 | -5.2392 | 1.5000 | 8.2392 | FALSE |
| GT1 | LRPPI2 | -5.0392 | 1.7000 | 8.4392 | FALSE |
| GT1 | LRPPI3 | -4.9392 | 1.8000 | 8.5392 | FALSE |
| GT1 | LRPPI4 | -5.4392 | 1.3000 | 8.0392 | FALSE |
| GT1 | ME1 | -2.4392 | 4.3000 | 11.0392 | FALSE |
| GT2 | GT3 | -5.8392 | 0.9000 | 7.6392 | FALSE |
| GT2 | HW | -6.2392 | 0.5000 | 7.2392 | FALSE |
| GT2 | KL | -6.9392 | -0.2000 | 6.5392 | FALSE |
| GT2 | LRPPI1 | -5.5392 | 1.2000 | 7.9392 | FALSE |
| GT2 | LRPPI2 | -5.3392 | 1.4000 | 8.1392 | FALSE |
| GT2 | LRPPI3 | -5.2392 | 1.5000 | 8.2392 | FALSE |
| GT2 | LRPPI4 | -5.7392 | 1.0000 | 7.7392 | FALSE |
| GT2 | ME1 | -2.7392 | 4.0000 | 10.7392 | FALSE |
| GT3 | HW | -7.1392 | -0.4000 | 6.3392 | FALSE |
| GT3 | KL | -7.8392 | -1.1000 | 5.6392 | FALSE |
| GT3 | LRPPI1 | -6.4392 | 0.3000 | 7.0392 | FALSE |
| GT3 | LRPPI2 | -6.2392 | 0.5000 | 7.2392 | FALSE |
| GT3 | LRPPI3 | -6.1392 | 0.6000 | 7.3392 | FALSE |
| GT3 | LRPPI4 | -6.6392 | 0.1000 | 6.8392 | FALSE |
| GT3 | ME1 | -3.6392 | 3.1000 | 9.8392 | FALSE |
| HW | KL | -7.4392 | -0.7000 | 6.0392 | FALSE |
| HW | LRPPI1 | -6.0392 | 0.7000 | 7.4392 | FALSE |
| HW | LRPPI2 | -5.8392 | 0.9000 | 7.6392 | FALSE |
| HW | LRPPI3 | -5.7392 | 1.0000 | 7.7392 | FALSE |
| HW | LRPPI4 | -6.2392 | 0.5000 | 7.2392 | FALSE |
| HW | ME1 | -3.2392 | 3.5000 | 10.2392 | FALSE |
| KL | LRPPI1 | -5.3392 | 1.4000 | 8.1392 | FALSE |
| KL | LRPPI2 | -5.1392 | 1.6000 | 8.3392 | FALSE |
| KL | LRPPI3 | -5.0392 | 1.7000 | 8.4392 | FALSE |
| KL | LRPPI4 | -5.5392 | 1.2000 | 7.9392 | FALSE |
| KL | ME1 | -2.5392 | 4.2000 | 10.9392 | FALSE |
| LRPPI1 | LRPPI2 | -6.5392 | 0.2000 | 6.9392 | FALSE |
| LRPPI1 | LRPPI3 | -6.4392 | 0.3000 | 7.0392 | FALSE |
| LRPPI1 | LRPPI4 | -6.9392 | -0.2000 | 6.5392 | FALSE |
| LRPPI1 | ME1 | -3.9392 | 2.8000 | 9.5392 | FALSE |
| LRPPI2 | LRPPI3 | -6.6392 | 0.1000 | 6.8392 | FALSE |
| LRPPI2 | LRPPI4 | -7.1392 | -0.4000 | 6.3392 | FALSE |
| LRPPI2 | ME1 | -4.1392 | 2.6000 | 9.3392 | FALSE |
| LRPPI3 | LRPPI4 | -7.2392 | -0.5000 | 6.2392 | FALSE |
| LRPPI3 | ME1 | -4.2392 | 2.5000 | 9.2392 | FALSE |
| LRPPI4 | ME1 | -3.7392 | 3.0000 | 9.7392 | FALSE |
Folds vs. Systems
The Friedman test was run in MATLAB against the accuracy for each fold.
Friedman's Anova Table
| Source | SS | df | MS | Chi-sq | Prob>Chi-sq |
|---|---|---|---|---|---|
| Columns | 208.167 | 10 | 20.8167 | 18.95 | 0.0409 |
| Error | 121.333 | 20 | 6.0667 | ||
| Total | 329.5 | 32 |
Tukey-Kramer HSD Multi-Comparison
The Tukey-Kramer HSD multi-comparison data below was generated using the following MATLAB instruction. Command: [c, m, h, gnames] = multicompare(stats, 'ctype', 'tukey-kramer', 'estimate', 'friedman', 'alpha', 0.05);
| TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
|---|---|---|---|---|---|
| GP1 | GT1 | -6.3762 | 2.3333 | 11.0429 | FALSE |
| GP1 | GT2 | -4.3762 | 4.3333 | 13.0429 | FALSE |
| GP1 | GT3 | -4.2095 | 4.5000 | 13.2095 | FALSE |
| GP1 | HW | -4.0429 | 4.6667 | 13.3762 | FALSE |
| GP1 | KL | -4.7095 | 4.0000 | 12.7095 | FALSE |
| GP1 | LRPPI1 | -3.3762 | 5.3333 | 14.0429 | FALSE |
| GP1 | LRPPI2 | -3.3762 | 5.3333 | 14.0429 | FALSE |
| GP1 | LRPPI3 | -1.2095 | 7.5000 | 16.2095 | FALSE |
| GP1 | LRPPI4 | -1.7095 | 7.0000 | 15.7095 | FALSE |
| GP1 | ME1 | 1.2905 | 10.0000 | 18.7095 | TRUE |
| GT1 | GT2 | -6.7095 | 2.0000 | 10.7095 | FALSE |
| GT1 | GT3 | -6.5429 | 2.1667 | 10.8762 | FALSE |
| GT1 | HW | -6.3762 | 2.3333 | 11.0429 | FALSE |
| GT1 | KL | -7.0429 | 1.6667 | 10.3762 | FALSE |
| GT1 | LRPPI1 | -5.7095 | 3.0000 | 11.7095 | FALSE |
| GT1 | LRPPI2 | -5.7095 | 3.0000 | 11.7095 | FALSE |
| GT1 | LRPPI3 | -3.5429 | 5.1667 | 13.8762 | FALSE |
| GT1 | LRPPI4 | -4.0429 | 4.6667 | 13.3762 | FALSE |
| GT1 | ME1 | -1.0429 | 7.6667 | 16.3762 | FALSE |
| GT2 | GT3 | -8.5429 | 0.1667 | 8.8762 | FALSE |
| GT2 | HW | -8.3762 | 0.3333 | 9.0429 | FALSE |
| GT2 | KL | -9.0429 | -0.3333 | 8.3762 | FALSE |
| GT2 | LRPPI1 | -7.7095 | 1.0000 | 9.7095 | FALSE |
| GT2 | LRPPI2 | -7.7095 | 1.0000 | 9.7095 | FALSE |
| GT2 | LRPPI3 | -5.5429 | 3.1667 | 11.8762 | FALSE |
| GT2 | LRPPI4 | -6.0429 | 2.6667 | 11.3762 | FALSE |
| GT2 | ME1 | -3.0429 | 5.6667 | 14.3762 | FALSE |
| GT3 | HW | -8.5429 | 0.1667 | 8.8762 | FALSE |
| GT3 | KL | -9.2095 | -0.5000 | 8.2095 | FALSE |
| GT3 | LRPPI1 | -7.8762 | 0.8333 | 9.5429 | FALSE |
| GT3 | LRPPI2 | -7.8762 | 0.8333 | 9.5429 | FALSE |
| GT3 | LRPPI3 | -5.7095 | 3.0000 | 11.7095 | FALSE |
| GT3 | LRPPI4 | -6.2095 | 2.5000 | 11.2095 | FALSE |
| GT3 | ME1 | -3.2095 | 5.5000 | 14.2095 | FALSE |
| HW | KL | -9.3762 | -0.6667 | 8.0429 | FALSE |
| HW | LRPPI1 | -8.0429 | 0.6667 | 9.3762 | FALSE |
| HW | LRPPI2 | -8.0429 | 0.6667 | 9.3762 | FALSE |
| HW | LRPPI3 | -5.8762 | 2.8333 | 11.5429 | FALSE |
| HW | LRPPI4 | -6.3762 | 2.3333 | 11.0429 | FALSE |
| HW | ME1 | -3.3762 | 5.3333 | 14.0429 | FALSE |
| KL | LRPPI1 | -7.3762 | 1.3333 | 10.0429 | FALSE |
| KL | LRPPI2 | -7.3762 | 1.3333 | 10.0429 | FALSE |
| KL | LRPPI3 | -5.2095 | 3.5000 | 12.2095 | FALSE |
| KL | LRPPI4 | -5.7095 | 3.0000 | 11.7095 | FALSE |
| KL | ME1 | -2.7095 | 6.0000 | 14.7095 | FALSE |
| LRPPI1 | LRPPI2 | -8.7095 | 0.0000 | 8.7095 | FALSE |
| LRPPI1 | LRPPI3 | -6.5429 | 2.1667 | 10.8762 | FALSE |
| LRPPI1 | LRPPI4 | -7.0429 | 1.6667 | 10.3762 | FALSE |
| LRPPI1 | ME1 | -4.0429 | 4.6667 | 13.3762 | FALSE |
| LRPPI2 | LRPPI3 | -6.5429 | 2.1667 | 10.8762 | FALSE |
| LRPPI2 | LRPPI4 | -7.0429 | 1.6667 | 10.3762 | FALSE |
| LRPPI2 | ME1 | -4.0429 | 4.6667 | 13.3762 | FALSE |
| LRPPI3 | LRPPI4 | -9.2095 | -0.5000 | 8.2095 | FALSE |
| LRPPI3 | ME1 | -6.2095 | 2.5000 | 11.2095 | FALSE |
| LRPPI4 | ME1 | -5.7095 | 3.0000 | 11.7095 | FALSE |
