2009:Audio Tag Classification (Mood Set) Results

From MIREX Wiki

Introduction

These are the results for the 2009 running of the Audio Tag Classification (Mood Set) task. For background information about this task set please refer to the 2009:Audio_Tag_Classification page. The data was created by Xiao Hu and consists of 3,469 unique songs and 135 mood tags organized into 18 mood tag groups.

Mood tags

The tags were collected from last.fm. All tags in this set are mood related as identified and grouped by WordNet-Affect and human experts.

Each mood tag group contains the following tags:

   * G12: calm, comfort, quiet, serene, mellow, chill out, calm down, calming, chillout, comforting, content, cool down, mellow music,  mellow rock, peace of mind, quietness, relaxation, serenity, solace, soothe, soothing, still, tranquil, tranquility, tranquility
   * G15: sad, sadness, unhappy, melancholic, melancholy, feeling sad, mood: sad ΓÇô slightly, sad song
   * G5: happy, happiness, happy songs, happy music, glad, mood: happy
   * G32: romantic, romantic music
   * G2: upbeat, gleeful, high spirits, zest, enthusiastic, buoyancy, elation, mood: upbeat
   * G16: depressed, blue, dark, depressive, dreary, gloom, darkness, depress, depression, depressing, gloomy
   * G28: anger, angry, choleric, fury, outraged, rage, angry music
   * G17: grief, heartbreak, mournful, sorrow, sorry, doleful, heartache, heartbreaking, heartsick, lachrymose, mourning, plaintive, regret, sorrowful
   * G14: dreamy
   * G6: cheerful, cheer up, festive, jolly, jovial, merry, cheer, cheering, cheery, get happy, rejoice, songs that are cheerful, sunny
   * G8: brooding, contemplative, meditative, reflective, broody, pensive, pondering, wistful
   * G29: aggression, aggressive
   * G25: angst, anxiety, anxious, jumpy, nervous, angsty
   * G9: confident, encouraging,  encouragement, optimism, optimistic
   * G7: desire, hope, hopeful, mood: hopeful
   * G11: earnest, heartfelt
   * G31: pessimism, cynical, pessimistic, weltschmerz, cynical/sarcastic
   * G1: excitement, exciting, exhilarating, thrill, ardor, stimulating, thrilling, titillating

For details on the mood tag groups, please see

X. Hu, J. S. Downie, A.Ehmann (2009). Lyric Text Mining in Music Mood Classification, In the 10th International Symposium on Music Information Retrieval (ISMIR 2009), Oct. 2009, Kobe, Japan

Data

The songs are Western pop songs mostly from the USPOP collection. Each song may belong to multiple mood tag groups. The main rationale on songs selection is: if more than one tag in a group were applied to a song, or if one tag in a group was applied more than once to a song, this song is marked as belonging to this group.

For details on how the songs were selected, please see the Mood multi-tag data description.

Audio format: 30 second clips, 44.1kHz, stereo,16bit, WAV files; The data were split into 3 folds with artist filtering.




General Legend

Team ID

BP1 = Juan José Burred, Geoffroy Peeters
BP2 = Juan José Burred, Geoffroy Peeters
CC1 = Chuan Cao, Ming Li
CC2 = Chuan Cao, Ming Li
CC3 = Chuan Cao, Ming Li
CC4 = Chuan Cao, Ming Li
GP = Geoffroy Peeters
GT1 = George Tzanetakis
GT2 = George Tzanetakis
HCB = Matthew D.Hoffman, David M. Blei, Perry R.Cook
LWW1 = Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang
LWW2 = Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang

Overall Summary Results (Binary)

Measure BP1 BP2 CC1 CC2 CC3 CC4 GP GT1 GT2 HCB LWW1 LWW2
Average Tag F-measure 0.195 0.193 0.172 0.180 0.147 0.183 0.084 0.211 0.209 0.063 0.204 0.219
Average Tag Accuracy 0.837 0.829 0.878 0.882 0.882 0.862 0.863 0.823 0.824 0.909 0.882 0.887
Average Positive Tag Accuracy 0.287 0.296 0.201 0.210 0.151 0.234 0.098 0.318 0.314 0.057 0.204 0.220
Average Negative Tag Accuracy 0.818 0.802 0.894 0.894 0.919 0.870 0.951 0.810 0.811 0.979 0.923 0.926

download these results as csv


Summary Binary Relevance F-Measure (Average Across All Folds)

Tag Positive Examples Negative Examples BP1 BP2 CC1 CC2 CC3 CC4 GP GT1 GT2 HCB LWW1 LWW2
g9 61.000 3404.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.033 0.022 0.000 0.033 0.017
g7 45.000 3420.000 0.000 0.000 0.000 0.000 0.000 0.000 0.043 0.000 0.015 0.000 0.023 0.000
g8 116.000 3349.000 0.023 0.011 0.000 0.000 0.017 0.037 0.027 0.052 0.029 0.000 0.086 0.052
g11 40.000 3425.000 0.000 0.000 0.000 0.000 0.000 0.000 0.013 0.000 0.000 0.000 0.000 0.000
g29 115.000 3350.000 0.297 0.313 0.171 0.167 0.070 0.110 0.145 0.267 0.255 0.000 0.294 0.335
g16 470.000 2995.000 0.280 0.249 0.210 0.186 0.159 0.224 0.036 0.217 0.231 0.000 0.276 0.291
g17 183.000 3282.000 0.054 0.050 0.020 0.029 0.019 0.044 0.043 0.157 0.149 0.000 0.060 0.076
g28 254.000 3211.000 0.391 0.403 0.391 0.364 0.282 0.317 0.184 0.298 0.312 0.000 0.346 0.400
g25 80.000 3385.000 0.000 0.000 0.026 0.000 0.022 0.023 0.011 0.085 0.042 0.000 0.050 0.051
g12 1678.000 1787.000 0.665 0.656 0.677 0.693 0.642 0.687 0.125 0.659 0.659 0.691 0.677 0.685
g14 146.000 3319.000 0.099 0.050 0.000 0.027 0.000 0.093 0.078 0.142 0.119 0.000 0.124 0.131
g15 1175.000 2290.000 0.573 0.547 0.527 0.591 0.473 0.571 0.296 0.577 0.581 0.440 0.581 0.601
g2 543.000 2922.000 0.334 0.324 0.353 0.369 0.333 0.368 0.114 0.374 0.374 0.007 0.321 0.361
g1 30.000 3435.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.044 0.022 0.000 0.000 0.000
g6 142.000 3323.000 0.018 0.064 0.034 0.000 0.037 0.030 0.096 0.057 0.070 0.000 0.057 0.120
g5 749.000 2716.000 0.404 0.396 0.422 0.426 0.390 0.425 0.106 0.395 0.403 0.000 0.393 0.426
g32 618.000 2847.000 0.370 0.403 0.268 0.384 0.204 0.370 0.140 0.377 0.385 0.000 0.345 0.378
g31 38.000 3427.000 0.000 0.000 0.000 0.000 0.000 0.000 0.054 0.070 0.089 0.000 0.000 0.026

download these results as csv

Summary Binary Accuracy (Average Across All Folds)

Tag Positive Examples Negative Examples BP1 BP2 CC1 CC2 CC3 CC4 GP GT1 GT2 HCB LWW1 LWW2
g9 61.000 3404.000 0.979 0.980 0.982 0.982 0.982 0.982 0.972 0.950 0.949 0.982 0.966 0.965
g7 45.000 3420.000 0.987 0.986 0.987 0.987 0.987 0.987 0.971 0.962 0.962 0.987 0.975 0.974
g8 116.000 3349.000 0.957 0.958 0.966 0.965 0.966 0.957 0.945 0.906 0.903 0.966 0.939 0.936
g11 40.000 3425.000 0.988 0.988 0.988 0.988 0.988 0.988 0.970 0.966 0.966 0.988 0.977 0.977
g29 115.000 3350.000 0.955 0.953 0.944 0.964 0.949 0.949 0.956 0.927 0.926 0.967 0.953 0.956
g16 470.000 2995.000 0.710 0.720 0.820 0.811 0.824 0.737 0.852 0.681 0.687 0.864 0.803 0.808
g17 183.000 3282.000 0.919 0.935 0.945 0.942 0.942 0.908 0.914 0.866 0.865 0.947 0.900 0.902
g28 254.000 3211.000 0.916 0.903 0.892 0.913 0.895 0.885 0.906 0.846 0.849 0.926 0.905 0.912
g25 80.000 3385.000 0.968 0.973 0.976 0.977 0.975 0.974 0.963 0.937 0.934 0.977 0.956 0.956
g12 1678.000 1787.000 0.528 0.494 0.575 0.608 0.596 0.613 0.533 0.505 0.506 0.701 0.687 0.695
g14 146.000 3319.000 0.932 0.945 0.957 0.956 0.955 0.939 0.907 0.892 0.889 0.958 0.926 0.927
g15 1175.000 2290.000 0.529 0.453 0.602 0.622 0.632 0.609 0.691 0.570 0.573 0.712 0.716 0.730
g2 543.000 2922.000 0.679 0.637 0.751 0.774 0.777 0.727 0.829 0.706 0.706 0.844 0.788 0.800
g1 30.000 3435.000 0.991 0.990 0.991 0.991 0.991 0.991 0.977 0.976 0.975 0.991 0.982 0.982
g6 142.000 3323.000 0.951 0.955 0.951 0.957 0.947 0.935 0.932 0.885 0.886 0.959 0.923 0.928
g5 749.000 2716.000 0.509 0.451 0.706 0.703 0.718 0.661 0.782 0.607 0.613 0.784 0.738 0.752
g32 618.000 2847.000 0.582 0.616 0.776 0.738 0.770 0.682 0.797 0.666 0.670 0.822 0.766 0.778
g31 38.000 3427.000 0.985 0.985 0.988 0.989 0.987 0.988 0.632 0.970 0.971 0.989 0.978 0.979

download these results as csv

Summary Positive Example Accuracy (Average Across All Folds)

Tag Positive Examples Negative Examples BP1 BP2 CC1 CC2 CC3 CC4 GP GT1 GT2 HCB LWW1 LWW2
g9 61.000 3404.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.050 0.034 0.000 0.034 0.019
g7 45.000 3420.000 0.000 0.000 0.000 0.000 0.000 0.000 0.070 0.000 0.021 0.000 0.022 0.000
g8 116.000 3349.000 0.019 0.008 0.000 0.000 0.009 0.028 0.030 0.080 0.043 0.000 0.082 0.054
g11 40.000 3425.000 0.000 0.000 0.000 0.000 0.000 0.000 0.022 0.000 0.000 0.000 0.000 0.000
g29 115.000 3350.000 0.285 0.324 0.170 0.128 0.063 0.108 0.126 0.396 0.379 0.000 0.293 0.334
g16 470.000 2995.000 0.430 0.349 0.180 0.162 0.125 0.290 0.022 0.332 0.353 0.000 0.279 0.295
g17 183.000 3282.000 0.055 0.033 0.011 0.016 0.011 0.039 0.045 0.236 0.224 0.000 0.061 0.076
g28 254.000 3211.000 0.370 0.448 0.474 0.343 0.278 0.365 0.176 0.448 0.472 0.000 0.346 0.400
g25 80.000 3385.000 0.000 0.000 0.014 0.000 0.014 0.014 0.013 0.122 0.061 0.000 0.051 0.052
g12 1678.000 1787.000 0.970 0.997 0.921 0.916 0.749 0.878 0.073 0.985 0.985 0.693 0.678 0.686
g14 146.000 3319.000 0.099 0.035 0.000 0.015 0.000 0.076 0.126 0.208 0.174 0.000 0.121 0.130
g15 1175.000 2290.000 0.933 0.968 0.657 0.810 0.490 0.773 0.232 0.869 0.875 0.336 0.584 0.603
g2 543.000 2922.000 0.529 0.558 0.435 0.425 0.356 0.508 0.077 0.563 0.564 0.003 0.322 0.361
g1 30.000 3435.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.067 0.033 0.000 0.000 0.000
g6 142.000 3323.000 0.016 0.038 0.021 0.000 0.030 0.030 0.108 0.084 0.106 0.000 0.058 0.121
g5 749.000 2716.000 0.775 0.838 0.497 0.510 0.419 0.583 0.064 0.602 0.613 0.000 0.397 0.431
g32 618.000 2847.000 0.690 0.732 0.234 0.461 0.167 0.527 0.110 0.571 0.582 0.000 0.348 0.380
g31 38.000 3427.000 0.000 0.000 0.000 0.000 0.000 0.000 0.472 0.112 0.136 0.000 0.000 0.024

download these results as csv

Summary Negative Example Accuracy (Average Across All Folds)

Tag Positive Examples Negative Examples BP1 BP2 CC1 CC2 CC3 CC4 GP GT1 GT2 HCB LWW1 LWW2
g9 61.000 3404.000 0.997 0.998 1.000 1.000 1.000 0.999 0.989 0.966 0.966 1.000 0.983 0.982
g7 45.000 3420.000 1.000 0.999 1.000 1.000 1.000 1.000 0.983 0.975 0.975 1.000 0.987 0.987
g8 116.000 3349.000 0.989 0.991 1.000 0.999 0.999 0.989 0.977 0.934 0.933 1.000 0.968 0.967
g11 40.000 3425.000 1.000 0.999 1.000 1.000 1.000 1.000 0.981 0.978 0.978 1.000 0.988 0.988
g29 115.000 3350.000 0.978 0.974 0.971 0.992 0.980 0.978 0.984 0.945 0.944 1.000 0.976 0.977
g16 470.000 2995.000 0.756 0.779 0.920 0.913 0.934 0.807 0.982 0.736 0.740 1.000 0.886 0.889
g17 183.000 3282.000 0.968 0.985 0.997 0.993 0.994 0.957 0.963 0.901 0.901 1.000 0.947 0.948
g28 254.000 3211.000 0.959 0.939 0.925 0.959 0.944 0.926 0.963 0.878 0.879 1.000 0.949 0.953
g25 80.000 3385.000 0.991 0.996 0.999 1.000 0.997 0.996 0.985 0.957 0.955 1.000 0.977 0.977
g12 1678.000 1787.000 0.113 0.024 0.251 0.320 0.453 0.366 0.967 0.059 0.059 0.710 0.696 0.705
g14 146.000 3319.000 0.969 0.985 0.999 0.998 0.997 0.977 0.941 0.921 0.920 1.000 0.962 0.962
g15 1175.000 2290.000 0.321 0.191 0.572 0.524 0.704 0.522 0.925 0.418 0.421 0.906 0.785 0.796
g2 543.000 2922.000 0.708 0.652 0.810 0.839 0.854 0.767 0.969 0.734 0.733 1.000 0.875 0.882
g1 30.000 3435.000 1.000 0.999 1.000 1.000 0.999 1.000 0.985 0.984 0.983 1.000 0.991 0.991
g6 142.000 3323.000 0.991 0.994 0.990 0.998 0.986 0.973 0.967 0.919 0.919 1.000 0.960 0.962
g5 749.000 2716.000 0.439 0.347 0.761 0.753 0.799 0.682 0.980 0.612 0.615 1.000 0.833 0.842
g32 618.000 2847.000 0.558 0.593 0.895 0.799 0.901 0.716 0.946 0.688 0.690 1.000 0.857 0.865
g31 38.000 3427.000 0.996 0.996 0.999 1.000 0.998 0.999 0.634 0.980 0.980 1.000 0.989 0.989

download these results as csv

Overall Summary Results (Affinity)

Measure BP1 BP2 CC1 CC2 CC3 CC4 GT1 GT2 HCB LWW1 LWW2
Average AUC-ROC Tag 0.648 0.632 0.652 0.681 0.629 0.646 0.649 0.655 0.664 0.667 0.701
Average AUC-ROC Clip 0.854 0.859 0.849 0.848 0.812 0.812 0.860 0.861 0.861 0.678 0.704
Precision at 3 0.383 0.389 0.392 0.392 0.368 0.368 0.381 0.384 0.385 0.215 0.238
Precision at 6 0.257 0.259 0.256 0.256 0.240 0.240 0.261 0.260 0.260 0.182 0.193
Precision at 9 0.189 0.190 0.186 0.186 0.178 0.178 0.192 0.192 0.192 0.153 0.158
Precision at 12 0.149 0.150 0.146 0.146 0.142 0.142 0.150 0.150 0.151 0.131 0.134
Precision at 15 0.122 0.123 0.121 0.121 0.119 0.119 0.123 0.123 0.123 0.116 0.117

download these results as csv

Summary AUC-ROC Tag (Average Across All Folds)

Tag BP1 BP2 CC1 CC2 CC3 CC4 GT1 GT2 HCB LWW1 LWW2
g9 0.508 0.527 0.574 0.627 0.564 0.576 0.474 0.499 0.521 0.534 0.558
g7 0.580 0.523 0.569 0.622 0.525 0.510 0.494 0.577 0.587 0.588 0.535
g8 0.577 0.578 0.562 0.609 0.558 0.624 0.601 0.574 0.589 0.608 0.627
g11 0.568 0.471 0.516 0.531 0.544 0.542 0.521 0.530 0.509 0.508 0.551
g29 0.775 0.844 0.833 0.850 0.780 0.783 0.854 0.857 0.837 0.874 0.888
g16 0.611 0.610 0.610 0.610 0.581 0.586 0.556 0.563 0.500 0.662 0.679
g17 0.609 0.589 0.599 0.625 0.516 0.532 0.676 0.662 0.663 0.611 0.680
g28 0.734 0.785 0.805 0.809 0.741 0.742 0.776 0.783 0.773 0.809 0.823
g25 0.668 0.615 0.694 0.747 0.658 0.677 0.685 0.682 0.663 0.709 0.717
g12 0.742 0.728 0.642 0.729 0.639 0.690 0.714 0.710 0.754 0.752 0.766
g14 0.638 0.618 0.667 0.716 0.606 0.661 0.701 0.697 0.716 0.706 0.731
g15 0.761 0.764 0.655 0.734 0.649 0.710 0.729 0.718 0.738 0.753 0.772
g2 0.681 0.670 0.721 0.731 0.705 0.700 0.724 0.722 0.720 0.724 0.747
g1 0.599 0.435 0.595 0.563 0.660 0.619 0.611 0.631 0.666 0.518 0.673
g6 0.572 0.573 0.629 0.636 0.610 0.616 0.589 0.585 0.606 0.608 0.655
g5 0.666 0.651 0.697 0.699 0.674 0.677 0.645 0.654 0.684 0.707 0.735
g32 0.681 0.718 0.667 0.703 0.622 0.668 0.694 0.697 0.697 0.715 0.743
g31 0.702 0.675 0.698 0.721 0.685 0.715 0.638 0.646 0.738 0.618 0.741

download these results as csv

Select Friedman's Test Results

Tag F-measure (Binary) Friedman Test

The following table and plot show the results of Friedman's ANOVA with Tukey-Kramer multiple comparisons computed over the F-measure for each tag in the test, averaged over all folds.

TeamID TeamID Lowerbound Mean Upperbound Significance
LWW2 GT1 -2.626 1.028 4.682 FALSE
LWW2 GT2 -2.904 0.750 4.404 FALSE
LWW2 LWW1 -1.849 1.806 5.460 FALSE
LWW2 BP1 -0.460 3.194 6.849 FALSE
LWW2 BP2 -0.404 3.250 6.904 FALSE
LWW2 CC4 -0.487 3.167 6.821 FALSE
LWW2 CC2 -0.154 3.500 7.154 FALSE
LWW2 CC1 0.512 4.167 7.821 TRUE
LWW2 CC3 2.068 5.722 9.376 TRUE
LWW2 GP 0.762 4.417 8.071 TRUE
LWW2 HCB 3.013 6.667 10.321 TRUE
GT1 GT2 -3.932 -0.278 3.376 FALSE
GT1 LWW1 -2.876 0.778 4.432 FALSE
GT1 BP1 -1.488 2.167 5.821 FALSE
GT1 BP2 -1.432 2.222 5.876 FALSE
GT1 CC4 -1.515 2.139 5.793 FALSE
GT1 CC2 -1.182 2.472 6.126 FALSE
GT1 CC1 -0.515 3.139 6.793 FALSE
GT1 CC3 1.040 4.694 8.349 TRUE
GT1 GP -0.265 3.389 7.043 FALSE
GT1 HCB 1.985 5.639 9.293 TRUE
GT2 LWW1 -2.599 1.056 4.710 FALSE
GT2 BP1 -1.210 2.444 6.099 FALSE
GT2 BP2 -1.154 2.500 6.154 FALSE
GT2 CC4 -1.238 2.417 6.071 FALSE
GT2 CC2 -0.904 2.750 6.404 FALSE
GT2 CC1 -0.237 3.417 7.071 FALSE
GT2 CC3 1.318 4.972 8.626 TRUE
GT2 GP 0.013 3.667 7.321 TRUE
GT2 HCB 2.263 5.917 9.571 TRUE
LWW1 BP1 -2.265 1.389 5.043 FALSE
LWW1 BP2 -2.210 1.444 5.099 FALSE
LWW1 CC4 -2.293 1.361 5.015 FALSE
LWW1 CC2 -1.960 1.694 5.349 FALSE
LWW1 CC1 -1.293 2.361 6.015 FALSE
LWW1 CC3 0.263 3.917 7.571 TRUE
LWW1 GP -1.043 2.611 6.265 FALSE
LWW1 HCB 1.207 4.861 8.515 TRUE
BP1 BP2 -3.599 0.056 3.710 FALSE
BP1 CC4 -3.682 -0.028 3.626 FALSE
BP1 CC2 -3.349 0.306 3.960 FALSE
BP1 CC1 -2.682 0.972 4.626 FALSE
BP1 CC3 -1.126 2.528 6.182 FALSE
BP1 GP -2.432 1.222 4.876 FALSE
BP1 HCB -0.182 3.472 7.126 FALSE
BP2 CC4 -3.737 -0.083 3.571 FALSE
BP2 CC2 -3.404 0.250 3.904 FALSE
BP2 CC1 -2.737 0.917 4.571 FALSE
BP2 CC3 -1.182 2.472 6.126 FALSE
BP2 GP -2.487 1.167 4.821 FALSE
BP2 HCB -0.237 3.417 7.071 FALSE
CC4 CC2 -3.321 0.333 3.987 FALSE
CC4 CC1 -2.654 1.000 4.654 FALSE
CC4 CC3 -1.099 2.556 6.210 FALSE
CC4 GP -2.404 1.250 4.904 FALSE
CC4 HCB -0.154 3.500 7.154 FALSE
CC2 CC1 -2.987 0.667 4.321 FALSE
CC2 CC3 -1.432 2.222 5.876 FALSE
CC2 GP -2.737 0.917 4.571 FALSE
CC2 HCB -0.487 3.167 6.821 FALSE
CC1 CC3 -2.099 1.556 5.210 FALSE
CC1 GP -3.404 0.250 3.904 FALSE
CC1 HCB -1.154 2.500 6.154 FALSE
CC3 GP -4.960 -1.306 2.349 FALSE
CC3 HCB -2.710 0.944 4.599 FALSE
GP HCB -1.404 2.250 5.904 FALSE

download these results as csv


https://music-ir.org/mirex/results/2009/tag/Mood/small.binary_FMeasure.friedman.tukeyKramerHSD.png

Per Track F-measure (Binary) Friedman Test

The following table and plot show the results of Friedman's ANOVA with Tukey-Kramer multiple comparisons computed over the F-measure for each track in the test, averaged over all folds.

TeamID TeamID Lowerbound Mean Upperbound Significance
CC2 CC1 -0.174 0.079 0.331 FALSE
CC2 BP1 0.086 0.338 0.590 TRUE
CC2 BP2 0.167 0.420 0.672 TRUE
CC2 CC4 0.264 0.516 0.768 TRUE
CC2 GT2 0.360 0.613 0.865 TRUE
CC2 GT1 0.463 0.716 0.968 TRUE
CC2 CC3 0.651 0.903 1.156 TRUE
CC2 LWW2 0.678 0.931 1.183 TRUE
CC2 LWW1 0.896 1.149 1.401 TRUE
CC2 HCB 2.081 2.334 2.586 TRUE
CC2 GP 3.503 3.756 4.008 TRUE
CC1 BP1 0.007 0.259 0.512 TRUE
CC1 BP2 0.089 0.341 0.593 TRUE
CC1 CC4 0.185 0.438 0.690 TRUE
CC1 GT2 0.282 0.534 0.786 TRUE
CC1 GT1 0.385 0.637 0.889 TRUE
CC1 CC3 0.573 0.825 1.077 TRUE
CC1 LWW2 0.600 0.852 1.105 TRUE
CC1 LWW1 0.818 1.070 1.322 TRUE
CC1 HCB 2.003 2.255 2.507 TRUE
CC1 GP 3.425 3.677 3.929 TRUE
BP1 BP2 -0.170 0.082 0.334 FALSE
BP1 CC4 -0.074 0.178 0.431 FALSE
BP1 GT2 0.023 0.275 0.527 TRUE
BP1 GT1 0.126 0.378 0.630 TRUE
BP1 CC3 0.313 0.566 0.818 TRUE
BP1 LWW2 0.341 0.593 0.845 TRUE
BP1 LWW1 0.558 0.811 1.063 TRUE
BP1 HCB 1.744 1.996 2.248 TRUE
BP1 GP 3.166 3.418 3.670 TRUE
BP2 CC4 -0.156 0.097 0.349 FALSE
BP2 GT2 -0.059 0.193 0.445 FALSE
BP2 GT1 0.044 0.296 0.548 TRUE
BP2 CC3 0.232 0.484 0.736 TRUE
BP2 LWW2 0.259 0.511 0.763 TRUE
BP2 LWW1 0.477 0.729 0.981 TRUE
BP2 HCB 1.662 1.914 2.166 TRUE
BP2 GP 3.084 3.336 3.588 TRUE
CC4 GT2 -0.156 0.097 0.349 FALSE
CC4 GT1 -0.053 0.199 0.452 FALSE
CC4 CC3 0.135 0.387 0.640 TRUE
CC4 LWW2 0.162 0.415 0.667 TRUE
CC4 LWW1 0.380 0.632 0.885 TRUE
CC4 HCB 1.565 1.817 2.070 TRUE
CC4 GP 2.987 3.240 3.492 TRUE
GT2 GT1 -0.149 0.103 0.355 FALSE
GT2 CC3 0.038 0.291 0.543 TRUE
GT2 LWW2 0.066 0.318 0.570 TRUE
GT2 LWW1 0.283 0.536 0.788 TRUE
GT2 HCB 1.469 1.721 1.973 TRUE
GT2 GP 2.891 3.143 3.395 TRUE
GT1 CC3 -0.064 0.188 0.440 FALSE
GT1 LWW2 -0.037 0.215 0.467 FALSE
GT1 LWW1 0.181 0.433 0.685 TRUE
GT1 HCB 1.366 1.618 1.870 TRUE
GT1 GP 2.788 3.040 3.292 TRUE
CC3 LWW2 -0.225 0.027 0.280 FALSE
CC3 LWW1 -0.007 0.245 0.497 FALSE
CC3 HCB 1.178 1.430 1.682 TRUE
CC3 GP 2.600 2.852 3.104 TRUE
LWW2 LWW1 -0.035 0.218 0.470 FALSE
LWW2 HCB 1.151 1.403 1.655 TRUE
LWW2 GP 2.573 2.825 3.077 TRUE
LWW1 HCB 0.933 1.185 1.437 TRUE
LWW1 GP 2.355 2.607 2.860 TRUE
HCB GP 1.170 1.422 1.674 TRUE

download these results as csv


https://music-ir.org/mirex/results/2009/tag/Mood/small.binary_FMeasure_per_track.friedman.tukeyKramerHSD.png

Tag AUC-ROC (Affinity) Friedman Test

The following table and plot show the results of Friedman's ANOVA with Tukey-Kramer multiple comparisons computed over the Area Under the ROC curve (AUC-ROC) for each tag in the test, averaged over all folds.

TeamID TeamID Lowerbound Mean Upperbound Significance
LWW2 CC2 -1.669 1.889 5.447 FALSE
LWW2 LWW1 -0.614 2.944 6.503 FALSE
LWW2 HCB 0.497 4.056 7.614 TRUE
LWW2 GT2 1.497 5.056 8.614 TRUE
LWW2 CC1 1.497 5.056 8.614 TRUE
LWW2 GT1 1.831 5.389 8.947 TRUE
LWW2 BP1 1.831 5.389 8.947 TRUE
LWW2 CC4 1.608 5.167 8.725 TRUE
LWW2 BP2 2.553 6.111 9.669 TRUE
LWW2 CC3 3.053 6.611 10.169 TRUE
CC2 LWW1 -2.503 1.056 4.614 FALSE
CC2 HCB -1.392 2.167 5.725 FALSE
CC2 GT2 -0.392 3.167 6.725 FALSE
CC2 CC1 -0.392 3.167 6.725 FALSE
CC2 GT1 -0.058 3.500 7.058 FALSE
CC2 BP1 -0.058 3.500 7.058 FALSE
CC2 CC4 -0.281 3.278 6.836 FALSE
CC2 BP2 0.664 4.222 7.781 TRUE
CC2 CC3 1.164 4.722 8.281 TRUE
LWW1 HCB -2.447 1.111 4.670 FALSE
LWW1 GT2 -1.447 2.111 5.670 FALSE
LWW1 CC1 -1.447 2.111 5.670 FALSE
LWW1 GT1 -1.114 2.444 6.003 FALSE
LWW1 BP1 -1.114 2.444 6.003 FALSE
LWW1 CC4 -1.336 2.222 5.781 FALSE
LWW1 BP2 -0.392 3.167 6.725 FALSE
LWW1 CC3 0.108 3.667 7.225 TRUE
HCB GT2 -2.558 1.000 4.558 FALSE
HCB CC1 -2.558 1.000 4.558 FALSE
HCB GT1 -2.225 1.333 4.892 FALSE
HCB BP1 -2.225 1.333 4.892 FALSE
HCB CC4 -2.447 1.111 4.670 FALSE
HCB BP2 -1.503 2.056 5.614 FALSE
HCB CC3 -1.003 2.556 6.114 FALSE
GT2 CC1 -3.558 0.000 3.558 FALSE
GT2 GT1 -3.225 0.333 3.892 FALSE
GT2 BP1 -3.225 0.333 3.892 FALSE
GT2 CC4 -3.447 0.111 3.670 FALSE
GT2 BP2 -2.503 1.056 4.614 FALSE
GT2 CC3 -2.003 1.556 5.114 FALSE
CC1 GT1 -3.225 0.333 3.892 FALSE
CC1 BP1 -3.225 0.333 3.892 FALSE
CC1 CC4 -3.447 0.111 3.670 FALSE
CC1 BP2 -2.503 1.056 4.614 FALSE
CC1 CC3 -2.003 1.556 5.114 FALSE
GT1 BP1 -3.558 0.000 3.558 FALSE
GT1 CC4 -3.781 -0.222 3.336 FALSE
GT1 BP2 -2.836 0.722 4.281 FALSE
GT1 CC3 -2.336 1.222 4.781 FALSE
BP1 CC4 -3.781 -0.222 3.336 FALSE
BP1 BP2 -2.836 0.722 4.281 FALSE
BP1 CC3 -2.336 1.222 4.781 FALSE
CC4 BP2 -2.614 0.944 4.503 FALSE
CC4 CC3 -2.114 1.444 5.003 FALSE
BP2 CC3 -3.058 0.500 4.058 FALSE

download these results as csv

https://music-ir.org/mirex/results/2009/tag/Mood/small.affinity.AUC_ROC_TAG.friedman.tukeyKramerHSD.png


Per Track AUC-ROC (Affinity) Friedman Test

The following table and plot show the results of Friedman's ANOVA with Tukey-Kramer multiple comparisons computed over the Area Under the ROC curve (AUC-ROC) for each track/clip in the test, averaged over all folds.

TeamID TeamID Lowerbound Mean Upperbound Significance
GT2 HCB -0.198 0.038 0.275 FALSE
GT2 GT1 -0.124 0.112 0.349 FALSE
GT2 BP2 -0.059 0.177 0.414 FALSE
GT2 BP1 -0.012 0.224 0.461 FALSE
GT2 CC1 -0.237 -0.001 0.236 FALSE
GT2 CC2 -0.235 0.001 0.237 FALSE
GT2 CC4 0.607 0.844 1.080 TRUE
GT2 CC3 0.611 0.847 1.083 TRUE
GT2 LWW2 2.307 2.544 2.780 TRUE
GT2 LWW1 2.713 2.950 3.186 TRUE
HCB GT1 -0.163 0.074 0.310 FALSE
HCB BP2 -0.097 0.139 0.375 FALSE
HCB BP1 -0.051 0.186 0.422 FALSE
HCB CC1 -0.276 -0.039 0.197 FALSE
HCB CC2 -0.274 -0.037 0.199 FALSE
HCB CC4 0.569 0.805 1.041 TRUE
HCB CC3 0.572 0.808 1.044 TRUE
HCB LWW2 2.269 2.505 2.741 TRUE
HCB LWW1 2.675 2.911 3.147 TRUE
GT1 BP2 -0.171 0.065 0.301 FALSE
GT1 BP1 -0.124 0.112 0.348 FALSE
GT1 CC1 -0.349 -0.113 0.123 FALSE
GT1 CC2 -0.347 -0.111 0.125 FALSE
GT1 CC4 0.495 0.731 0.968 TRUE
GT1 CC3 0.498 0.735 0.971 TRUE
GT1 LWW2 2.195 2.432 2.668 TRUE
GT1 LWW1 2.601 2.837 3.074 TRUE
BP2 BP1 -0.190 0.047 0.283 FALSE
BP2 CC1 -0.414 -0.178 0.058 FALSE
BP2 CC2 -0.413 -0.176 0.060 FALSE
BP2 CC4 0.430 0.666 0.902 TRUE
BP2 CC3 0.433 0.669 0.906 TRUE
BP2 LWW2 2.130 2.366 2.603 TRUE
BP2 LWW1 2.536 2.772 3.008 TRUE
BP1 CC1 -0.461 -0.225 0.011 FALSE
BP1 CC2 -0.460 -0.223 0.013 FALSE
BP1 CC4 0.383 0.619 0.856 TRUE
BP1 CC3 0.386 0.623 0.859 TRUE
BP1 LWW2 2.083 2.320 2.556 TRUE
BP1 LWW1 2.489 2.725 2.962 TRUE
CC1 CC2 -0.235 0.002 0.238 FALSE
CC1 CC4 0.608 0.844 1.081 TRUE
CC1 CC3 0.611 0.848 1.084 TRUE
CC1 LWW2 2.308 2.544 2.781 TRUE
CC1 LWW1 2.714 2.950 3.187 TRUE
CC2 CC4 0.606 0.843 1.079 TRUE
CC2 CC3 0.610 0.846 1.082 TRUE
CC2 LWW2 2.306 2.543 2.779 TRUE
CC2 LWW1 2.712 2.949 3.185 TRUE
CC4 CC3 -0.233 0.003 0.239 FALSE
CC4 LWW2 1.464 1.700 1.936 TRUE
CC4 LWW1 1.870 2.106 2.342 TRUE
CC3 LWW2 1.461 1.697 1.933 TRUE
CC3 LWW1 1.867 2.103 2.339 TRUE
LWW2 LWW1 0.170 0.406 0.642 TRUE

download these results as csv

https://music-ir.org/mirex/results/2009/tag/Mood/small.affinity.AUC_ROC_TRACK.friedman.tukeyKramerHSD.png

Assorted Results Files for Download

General Results

affinity_tag_fold_AUC_ROC.csv
affinity_clip_AUC_ROC.csv
binary_per_fold_Accuracy.csv
binary_per_fold_Fmeasure.csv
binary_per_fold_negative_example_Accuracy.csv
binary_per_fold_per_track_Accuracy.csv
binary_per_fold_per_track_Fmeasure.csv
binary_per_fold_per_track_negative_example_Accuracy.csv
binary_per_fold_per_track_positive_example_Accuracy.csv
binary_per_fold_positive_example_Accuracy.csv

Friedman's Tests Results

affinity.PrecisionAt3.friedman.tukeyKramerHSD.csv
affinity.PrecisionAt3.friedman.tukeyKramerHSD.png
affinity.PrecisionAt6.friedman.tukeyKramerHSD.csv
affinity.PrecisionAt6.friedman.tukeyKramerHSD.png
affinity.PrecisionAt9.friedman.tukeyKramerHSD.csv
affinity.PrecisionAt9.friedman.tukeyKramerHSD.png
affinity.PrecisionAt12.friedman.tukeyKramerHSD.csv
affinity.PrecisionAt12.friedman.tukeyKramerHSD.png
affinity.PrecisionAt15.friedman.tukeyKramerHSD.csv
affinity.PrecisionAt15.friedman.tukeyKramerHSD.png
binary_Accuracy.friedman.tukeyKramerHSD.csv
binary_Accuracy.friedman.tukeyKramerHSD.png

Results By Algorithm

(.tgz format)

BP1 = Juan José Burred, Geoffroy Peeters
BP2 = Juan José Burred, Geoffroy Peeters
CC1 = Chuan Cao, Ming Li
CC2 = Chuan Cao, Ming Li
CC3 = Chuan Cao, Ming Li
CC4 = Chuan Cao, Ming Li
GP = Geoffroy Peeters
GT1 = George Tzanetakis
GT2 = George Tzanetakis
LWW1 = Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang
LWW2 = Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang
HCB = Matthew D.Hoffman, David M. Blei, Perry R.Cook