Shuttle (version#01)
This dataset has been preprocessed in different variants in the literature. We follow the procedure of Zhang et al. [1], using classes 1, 3, 4, 5, 6 and 7 as inliers and class 2 as outlier, selecting 1000 inliers vs. 13 outliers (class 2). The selection of instances is based on the test set. The processed dataset consists of 1013 instances represented in 9 attributes, with 13 outliers (1.28%) and 1000 inliers (98.72%).
References:
[1] K. Zhang, M. Hutter, and H. Jin. A new local distance-based outlier detection approach for scattered real-world data. In Proc. PAKDD, pages 813-822, 2009.
Download all data set variants used (328.2 kB). You can also access the original data. (shuttle.tst, [1] only uses test set)
Normalized, without duplicates
This version contains 9 attributes, 1013 objects, 13 outliers (1.28%)
Download raw algorithm results (8.4 MB) Download raw algorithm evaluation table (46.3 kB)
Best Parameters
The following table contains the best
(overall and per-method)
results for each method and evaluation measure (when the same score was achieved twice, only the smallest k is given).
The Maximum F1-Measure is complimentary in addition to the measures in the original publication.
Algorithm | k | P@n | Adj. P@n | AP | Adj. AP | Max-F1 | Adj. MF1 | ROC AUC |
---|---|---|---|---|---|---|---|---|
KNN | 3 | 0.38462 | 0.37662 | 0.38600 | 0.37802 | 0.58537 | 0.57998 | 0.98908 |
KNN | 4 | 0.46154 | 0.45454 | 0.38494 | 0.37695 | 0.55319 | 0.54738 | 0.98746 |
KNNW | 3 | 0.38462 | 0.37662 | 0.30430 | 0.29526 | 0.51429 | 0.50797 | 0.91754 |
KNNW | 6 | 0.38462 | 0.37662 | 0.37464 | 0.36651 | 0.52941 | 0.52329 | 0.98592 |
KNNW | 7 | 0.38462 | 0.37662 | 0.37166 | 0.36349 | 0.48649 | 0.47981 | 0.98615 |
LOF | 6 | 0.30769 | 0.29869 | 0.31305 | 0.30412 | 0.56410 | 0.55844 | 0.92869 |
LOF | 9 | 0.23077 | 0.22077 | 0.37864 | 0.37056 | 0.66667 | 0.66233 | 0.98962 |
SimplifiedLOF | 9 | 0.38462 | 0.37662 | 0.29411 | 0.28494 | 0.46154 | 0.45454 | 0.98100 |
SimplifiedLOF | 11 | 0.38462 | 0.37662 | 0.33752 | 0.32891 | 0.53333 | 0.52727 | 0.98692 |
SimplifiedLOF | 15 | 0.23077 | 0.22077 | 0.31031 | 0.30135 | 0.55000 | 0.54415 | 0.98546 |
LoOP | 9 | 0.30769 | 0.29869 | 0.20080 | 0.19041 | 0.35897 | 0.35064 | 0.95631 |
LoOP | 20 | 0.30769 | 0.29869 | 0.34661 | 0.33812 | 0.57895 | 0.57347 | 0.98692 |
LDOF | 16 | 0.23077 | 0.22077 | 0.12299 | 0.11159 | 0.23077 | 0.22077 | 0.92469 |
LDOF | 57 | 0.15385 | 0.14285 | 0.25882 | 0.24919 | 0.47059 | 0.46371 | 0.97623 |
LDOF | 62 | 0.23077 | 0.22077 | 0.26086 | 0.25125 | 0.42424 | 0.41676 | 0.97662 |
LDOF | 77 | 0.15385 | 0.14285 | 0.25075 | 0.24101 | 0.39286 | 0.38496 | 0.97754 |
ODIN | 46 | 0.26923 | 0.25973 | 0.38724 | 0.37927 | 0.55814 | 0.55240 | 0.98885 |
ODIN | 56 | 0.33333 | 0.32467 | 0.38988 | 0.38195 | 0.55556 | 0.54978 | 0.98835 |
ODIN | 81 | 0.56410 | 0.55844 | 0.36564 | 0.35739 | 0.59259 | 0.58730 | 0.94096 |
FastABOD | 7 | 0.23077 | 0.22077 | 0.19030 | 0.17978 | 0.26471 | 0.25515 | 0.82708 |
FastABOD | 82 | 0.23077 | 0.22077 | 0.23937 | 0.22948 | 0.35714 | 0.34879 | 0.83646 |
FastABOD | 96 | 0.23077 | 0.22077 | 0.24103 | 0.23117 | 0.35714 | 0.34879 | 0.83754 |
FastABOD | 100 | 0.23077 | 0.22077 | 0.24086 | 0.23099 | 0.35714 | 0.34879 | 0.83815 |
KDEOS | 67 | 0.38462 | 0.37662 | 0.29315 | 0.28396 | 0.45714 | 0.45009 | 0.98108 |
KDEOS | 70 | 0.46154 | 0.45454 | 0.31823 | 0.30937 | 0.50000 | 0.49350 | 0.98062 |
KDEOS | 98 | 0.46154 | 0.45454 | 0.42922 | 0.42180 | 0.60000 | 0.59480 | 0.96577 |
KDEOS | 100 | 0.46154 | 0.45454 | 0.43398 | 0.42662 | 0.60000 | 0.59480 | 0.96600 |
LDF | 5 | 0.53846 | 0.53246 | 0.43072 | 0.42332 | 0.61538 | 0.61038 | 0.97462 |
LDF | 8 | 0.38462 | 0.37662 | 0.43793 | 0.43062 | 0.70270 | 0.69884 | 0.99223 |
INFLO | 6 | 0.30769 | 0.29869 | 0.20006 | 0.18967 | 0.36667 | 0.35843 | 0.88362 |
INFLO | 13 | 0.23077 | 0.22077 | 0.31486 | 0.30596 | 0.59459 | 0.58932 | 0.94100 |
INFLO | 15 | 0.23077 | 0.22077 | 0.34284 | 0.33430 | 0.59459 | 0.58932 | 0.98623 |
INFLO | 19 | 0.23077 | 0.22077 | 0.33360 | 0.32494 | 0.53659 | 0.53056 | 0.98631 |
COF | 16 | 0.53846 | 0.53246 | 0.40798 | 0.40028 | 0.59459 | 0.58932 | 0.98969 |
COF | 19 | 0.53846 | 0.53246 | 0.45899 | 0.45196 | 0.64865 | 0.64408 | 0.99177 |
COF | 20 | 0.53846 | 0.53246 | 0.46190 | 0.45491 | 0.64865 | 0.64408 | 0.99200 |
Plots
Not normalized, without duplicates
This version contains 9 attributes, 1013 objects, 13 outliers (1.28%)
Download raw algorithm results (8.3 MB) Download raw algorithm evaluation table (44.5 kB)
Best Parameters
The following table contains the best
(overall and per-method)
results for each method and evaluation measure (when the same score was achieved twice, only the smallest k is given).
The Maximum F1-Measure is complimentary in addition to the measures in the original publication.
Algorithm | k | P@n | Adj. P@n | AP | Adj. AP | Max-F1 | Adj. MF1 | ROC AUC |
---|---|---|---|---|---|---|---|---|
KNN | 2 | 0.23077 | 0.22077 | 0.14835 | 0.13728 | 0.25926 | 0.24963 | 0.80992 |
KNN | 5 | 0.23077 | 0.22077 | 0.18879 | 0.17824 | 0.30380 | 0.29475 | 0.96496 |
KNNW | 7 | 0.23077 | 0.22077 | 0.15511 | 0.14413 | 0.25806 | 0.24842 | 0.93515 |
KNNW | 9 | 0.23077 | 0.22077 | 0.15912 | 0.14819 | 0.25000 | 0.24025 | 0.94362 |
KNNW | 13 | 0.23077 | 0.22077 | 0.15514 | 0.14416 | 0.24000 | 0.23012 | 0.94585 |
LOF | 4 | 0.30769 | 0.29869 | 0.11507 | 0.10356 | 0.30769 | 0.29869 | 0.62969 |
LOF | 21 | 0.07692 | 0.06492 | 0.18285 | 0.17223 | 0.39130 | 0.38339 | 0.95715 |
LOF | 79 | 0.07692 | 0.06492 | 0.20549 | 0.19516 | 0.45455 | 0.44745 | 0.93685 |
LOF | 98 | 0.07692 | 0.06492 | 0.20225 | 0.19188 | 0.47619 | 0.46938 | 0.92308 |
SimplifiedLOF | 14 | 0.30769 | 0.29869 | 0.17533 | 0.16461 | 0.35714 | 0.34879 | 0.93385 |
SimplifiedLOF | 26 | 0.07692 | 0.06492 | 0.18432 | 0.17372 | 0.31579 | 0.30689 | 0.96754 |
SimplifiedLOF | 93 | 0.07692 | 0.06492 | 0.22147 | 0.21135 | 0.47619 | 0.46938 | 0.95954 |
SimplifiedLOF | 95 | 0.07692 | 0.06492 | 0.22065 | 0.21052 | 0.48780 | 0.48115 | 0.95746 |
LoOP | 2 | 0.23077 | 0.22077 | 0.09070 | 0.07888 | 0.28571 | 0.27643 | 0.69569 |
LoOP | 26 | 0.15385 | 0.14285 | 0.17358 | 0.16284 | 0.31579 | 0.30689 | 0.95992 |
LoOP | 97 | 0.07692 | 0.06492 | 0.20922 | 0.19894 | 0.44444 | 0.43722 | 0.95369 |
LoOP | 98 | 0.07692 | 0.06492 | 0.20959 | 0.19932 | 0.44444 | 0.43722 | 0.95385 |
LDOF | 3 | 0.23077 | 0.22077 | 0.09675 | 0.08501 | 0.30000 | 0.29090 | 0.51015 |
LDOF | 47 | 0.15385 | 0.14285 | 0.18127 | 0.17063 | 0.33333 | 0.32467 | 0.96377 |
LDOF | 91 | 0.07692 | 0.06492 | 0.18936 | 0.17882 | 0.40909 | 0.40141 | 0.95969 |
LDOF | 95 | 0.07692 | 0.06492 | 0.19040 | 0.17988 | 0.40000 | 0.39220 | 0.95938 |
ODIN | 47 | 0.26154 | 0.25194 | 0.25108 | 0.24135 | 0.45000 | 0.44285 | 0.93788 |
ODIN | 50 | 0.28994 | 0.28071 | 0.25128 | 0.24154 | 0.43902 | 0.43173 | 0.93050 |
FastABOD | 3 | 0.15385 | 0.14285 | 0.06976 | 0.05767 | 0.18750 | 0.17694 | 0.63615 |
FastABOD | 4 | 0.23077 | 0.22077 | 0.08641 | 0.07454 | 0.24000 | 0.23012 | 0.62692 |
KDEOS | 52 | 0.00000 | -0.01300 | 0.07039 | 0.05830 | 0.21212 | 0.20188 | 0.89346 |
KDEOS | 70 | 0.15385 | 0.14285 | 0.07662 | 0.06462 | 0.15385 | 0.14285 | 0.86031 |
KDEOS | 84 | 0.15385 | 0.14285 | 0.11446 | 0.10295 | 0.23529 | 0.22535 | 0.85262 |
KDEOS | 89 | 0.15385 | 0.14285 | 0.15401 | 0.14301 | 0.23529 | 0.22535 | 0.85615 |
LDF | 4 | 0.30769 | 0.29869 | 0.13649 | 0.12526 | 0.33333 | 0.32467 | 0.63923 |
LDF | 8 | 0.30769 | 0.29869 | 0.25542 | 0.24574 | 0.45000 | 0.44285 | 0.96023 |
LDF | 10 | 0.23077 | 0.22077 | 0.21041 | 0.20014 | 0.40816 | 0.40047 | 0.96662 |
LDF | 48 | 0.07692 | 0.06492 | 0.19742 | 0.18699 | 0.46154 | 0.45454 | 0.92331 |
INFLO | 10 | 0.30769 | 0.29869 | 0.12542 | 0.11405 | 0.30769 | 0.29869 | 0.83577 |
INFLO | 50 | 0.07692 | 0.06492 | 0.19598 | 0.18553 | 0.36667 | 0.35843 | 0.96585 |
INFLO | 68 | 0.07692 | 0.06492 | 0.20272 | 0.19236 | 0.39024 | 0.38232 | 0.96054 |
INFLO | 97 | 0.07692 | 0.06492 | 0.19693 | 0.18649 | 0.46512 | 0.45816 | 0.93685 |
COF | 2 | 0.23077 | 0.22077 | 0.07538 | 0.06336 | 0.26087 | 0.25126 | 0.61927 |
COF | 5 | 0.15385 | 0.14285 | 0.09903 | 0.08732 | 0.27586 | 0.26645 | 0.66462 |
COF | 26 | 0.15385 | 0.14285 | 0.15235 | 0.14133 | 0.25000 | 0.24025 | 0.95038 |