Data format

Data format for confusion matrix

Each line contains data for a KxK confusion matrix C, and it should be of the following format:

C_11 C_12 ... C_1K C_21 C_22 ... C_2K ... C_K1 C_K2 ... C_KK

Example for K=3:

213 21 12 89 459 90 29 39 958
984 58 23 239 929 59 95 12 894
34 3443 96 3467 89 32 13 49 3977

Data for two NxK tables

The K coordinates of each of the correspoding N vectors is listed side by side:

Y_n1, Y_n2, ... , Y_nK X_n1, X_n2, ... , X_nK

Example for K=4:

1.23297 14.3645 10.517 9.91405 0.49452 0.747626 1.28534 0.770936
15.7478 2.1789 12.6862 4.81075 0.892471 2.49287 1.01103 0.126026
5.6903 7.02067 2.27584 7.42615 1.12734 2.26421 1.12176 0.809775
18.068 7.48363 2.02963 4.69147 1.92054 2.77276 0.801278 0.117529
14.8858 28.178 1.84132 7.57969 2.2011 0.922135 1.68623 0.789104
2.27723 7.94528 3.50152 5.22574 1.83874 1.29179 1.85978 0.73886
31.8381 29.3393 4.29358 2.97694 1.03989 1.1619 0.403434 0.841058
2.91701 3.31743 16.9492 7.03813 0.0141235 0.00128557 1.873 0.967322
17.8455 29.1596 19.2678 0.87021 1.34492 2.9367 1.49967 0.143531
8.64643 25.5141 6.63087 5.54661 1.54247 2.67339 0.0343144 0.159415
15.7375 15.2169 4.99688 5.3168 1.14566 2.54189 1.31415 0.108773
14.3291 13.7913 18.5771 4.0899 1.33297 2.20165 1.70282 0.223556
6.51296 7.6467 0.257176 5.63135 3.48205 2.14088 1.00546 0.559662
32.9802 29.9874 10.4431 9.8184 1.64974 1.02698 0.162374 0.877139
34.2046 2.09384 7.34978 6.27463 0.0590457 0.649435 0.115073 0.130462
9.64171 2.65502 15.8463 7.95844 3.18509 2.19831 1.40019 0.146231
4.7287 2.44826 3.37259 5.04859 1.93504 0.700786 0.754252 0.593287
17.7502 23.259 6.5992 7.15579 2.42684 1.8716 1.56656 0.176719
27.3579 28.0138 9.30945 7.51888 2.39674 0.768776 0.730063 0.723259
7.31869 3.35467 10.4162 8.54055 2.35175 1.31804 1.32581 0.825728
3.22472 2.8043 13.1322 5.27124 0.963006 2.23045 0.606291 0.127651
5.08926 19.4816 12.6245 0.436619 1.54396 1.40153 0.688632 0.199431
10.769 19.1015 5.28355 2.78939 1.98167 1.65886 1.36683 0.924458
0.518364 24.1582 12.0223 3.9739 0.520645 2.49077 1.95297 0.094704
7.0525 10.3483 16.996 3.3356 2.26862 2.83284 1.07514 0.981324
30.2649 2.59751 16.0432 4.08872 0.130956 2.44806 1.98548 0.676687
24.4192 2.27855 16.5568 4.27026 2.73314 0.144949 1.54315 0.954542
2.65457 17.6153 8.82464 0.291691 1.87407 0.394262 1.9143 0.0377667
5.24974 23.6356 6.29959 5.55731 1.19686 1.80708 1.46002 0.857242
20.2651 4.13563 3.63032 5.67505 0.138728 1.13699 1.15686 0.847655
19.3748 22.4564 0.549747 5.22905 0.303436 2.27782 1.36747 0.696692
20.0786 3.09246 10.0094 6.30634 1.84355 1.31212 1.06416 0.708391
2.13334 27.094 4.73389 8.0385 2.99253 0.857101 0.53405 0.0236485
4.40929 27.3718 6.42533 3.54005 0.680103 0.488295 1.6789 0.449931
21.0353 10.6117 15.615 4.64033 2.0494 0.851773 0.476933 0.304831
35.6803 9.99718 7.24817 8.30925 3.84938 2.75848 1.91452 0.0885048
35.0544 5.74017 14.9414 0.462843 2.59458 1.13596 0.471794 0.742525
35.2152 1.85686 12.588 6.64083 0.172323 1.86453 0.93833 0.953536
28.0834 21.8871 5.04952 3.28335 0.35044 2.31403 0.936071 0.970001