Shuttle (version#03)
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 (8.6 MB) Download raw algorithm evaluation table (45.3 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 | 2 | 0.23077 | 0.22077 | 0.17581 | 0.16509 | 0.35000 | 0.34155 | 0.87415 |
KNN | 3 | 0.23077 | 0.22077 | 0.22509 | 0.21502 | 0.37931 | 0.37124 | 0.97338 |
KNNW | 4 | 0.23077 | 0.22077 | 0.16086 | 0.14995 | 0.25926 | 0.24963 | 0.91692 |
KNNW | 7 | 0.23077 | 0.22077 | 0.18337 | 0.17275 | 0.27451 | 0.26508 | 0.95762 |
KNNW | 9 | 0.23077 | 0.22077 | 0.18375 | 0.17314 | 0.26415 | 0.25458 | 0.95885 |
KNNW | 10 | 0.23077 | 0.22077 | 0.17783 | 0.16715 | 0.26415 | 0.25458 | 0.95931 |
LOF | 11 | 0.30769 | 0.29869 | 0.21717 | 0.20699 | 0.43750 | 0.43019 | 0.94762 |
LOF | 12 | 0.38462 | 0.37662 | 0.23468 | 0.22473 | 0.45161 | 0.44448 | 0.94600 |
SimplifiedLOF | 12 | 0.07692 | 0.06492 | 0.17465 | 0.16392 | 0.31818 | 0.30932 | 0.93785 |
SimplifiedLOF | 15 | 0.15385 | 0.14285 | 0.17464 | 0.16391 | 0.35556 | 0.34718 | 0.94231 |
SimplifiedLOF | 25 | 0.23077 | 0.22077 | 0.14290 | 0.13176 | 0.27586 | 0.26645 | 0.93492 |
SimplifiedLOF | 99 | 0.00000 | -0.01300 | 0.11379 | 0.10227 | 0.22500 | 0.21493 | 0.94469 |
LoOP | 18 | 0.23077 | 0.22077 | 0.18437 | 0.17377 | 0.32432 | 0.31554 | 0.94292 |
LoOP | 21 | 0.30769 | 0.29869 | 0.18147 | 0.17083 | 0.32000 | 0.31116 | 0.94531 |
LoOP | 22 | 0.30769 | 0.29869 | 0.18414 | 0.17354 | 0.34783 | 0.33935 | 0.94592 |
LoOP | 23 | 0.30769 | 0.29869 | 0.18422 | 0.17361 | 0.33333 | 0.32467 | 0.94685 |
LDOF | 24 | 0.07692 | 0.06492 | 0.15520 | 0.14422 | 0.33333 | 0.32467 | 0.89269 |
LDOF | 26 | 0.07692 | 0.06492 | 0.15817 | 0.14723 | 0.31034 | 0.30138 | 0.90531 |
LDOF | 41 | 0.23077 | 0.22077 | 0.11772 | 0.10625 | 0.23077 | 0.22077 | 0.89177 |
LDOF | 99 | 0.07692 | 0.06492 | 0.10387 | 0.09222 | 0.19355 | 0.18306 | 0.92600 |
ODIN | 10 | 0.15385 | 0.14285 | 0.06420 | 0.05203 | 0.15385 | 0.14285 | 0.86142 |
ODIN | 23 | 0.15385 | 0.14285 | 0.13246 | 0.12119 | 0.22535 | 0.21528 | 0.94146 |
ODIN | 26 | 0.15385 | 0.14285 | 0.14742 | 0.13633 | 0.24242 | 0.23258 | 0.94092 |
ODIN | 27 | 0.07692 | 0.06492 | 0.12372 | 0.11233 | 0.25000 | 0.24025 | 0.93246 |
FastABOD | 3 | 0.15385 | 0.14285 | 0.06457 | 0.05241 | 0.19048 | 0.17995 | 0.65508 |
FastABOD | 7 | 0.15385 | 0.14285 | 0.09528 | 0.08352 | 0.22222 | 0.21211 | 0.67177 |
FastABOD | 8 | 0.15385 | 0.14285 | 0.09624 | 0.08449 | 0.22222 | 0.21211 | 0.67400 |
FastABOD | 60 | 0.15385 | 0.14285 | 0.08633 | 0.07445 | 0.22222 | 0.21211 | 0.70285 |
KDEOS | 30 | 0.07692 | 0.06492 | 0.07230 | 0.06024 | 0.14966 | 0.13861 | 0.90677 |
KDEOS | 40 | 0.23077 | 0.22077 | 0.08692 | 0.07505 | 0.23077 | 0.22077 | 0.84723 |
KDEOS | 44 | 0.23077 | 0.22077 | 0.10398 | 0.09233 | 0.28571 | 0.27643 | 0.84562 |
KDEOS | 58 | 0.15385 | 0.14285 | 0.22122 | 0.21110 | 0.26667 | 0.25713 | 0.87200 |
LDF | 4 | 0.30769 | 0.29869 | 0.21040 | 0.20013 | 0.38710 | 0.37913 | 0.93562 |
LDF | 6 | 0.23077 | 0.22077 | 0.20338 | 0.19302 | 0.37838 | 0.37030 | 0.95708 |
LDF | 8 | 0.15385 | 0.14285 | 0.19699 | 0.18655 | 0.41026 | 0.40259 | 0.94646 |
INFLO | 14 | 0.30769 | 0.29869 | 0.16950 | 0.15870 | 0.32143 | 0.31261 | 0.92654 |
INFLO | 18 | 0.30769 | 0.29869 | 0.18049 | 0.16984 | 0.34783 | 0.33935 | 0.94123 |
COF | 17 | 0.15385 | 0.14285 | 0.16376 | 0.15289 | 0.25243 | 0.24271 | 0.94969 |
COF | 45 | 0.30769 | 0.29869 | 0.16846 | 0.15765 | 0.30769 | 0.29869 | 0.92523 |
COF | 48 | 0.23077 | 0.22077 | 0.15690 | 0.14594 | 0.31579 | 0.30689 | 0.92123 |
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 (44.4 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 | 0.30769 | 0.29869 | 0.20176 | 0.19138 | 0.34783 | 0.33935 | 0.95088 |
KNN | 9 | 0.30769 | 0.29869 | 0.25595 | 0.24628 | 0.38095 | 0.37290 | 0.97435 |
KNNW | 15 | 0.30769 | 0.29869 | 0.22195 | 0.21184 | 0.30769 | 0.29869 | 0.96477 |
LOF | 8 | 0.38462 | 0.37662 | 0.19004 | 0.17951 | 0.38462 | 0.37662 | 0.91754 |
LOF | 17 | 0.38462 | 0.37662 | 0.32767 | 0.31893 | 0.52941 | 0.52329 | 0.98100 |
LOF | 18 | 0.38462 | 0.37662 | 0.33111 | 0.32242 | 0.54545 | 0.53955 | 0.98100 |
SimplifiedLOF | 19 | 0.38462 | 0.37662 | 0.27240 | 0.26294 | 0.40816 | 0.40047 | 0.97608 |
SimplifiedLOF | 23 | 0.38462 | 0.37662 | 0.30379 | 0.29474 | 0.44898 | 0.44182 | 0.97969 |
SimplifiedLOF | 25 | 0.38462 | 0.37662 | 0.30991 | 0.30094 | 0.42857 | 0.42114 | 0.97892 |
LoOP | 25 | 0.30769 | 0.29869 | 0.27019 | 0.26070 | 0.42553 | 0.41806 | 0.97700 |
LoOP | 33 | 0.30769 | 0.29869 | 0.26637 | 0.25683 | 0.42857 | 0.42114 | 0.97269 |
LoOP | 35 | 0.30769 | 0.29869 | 0.28886 | 0.27961 | 0.42857 | 0.42114 | 0.97308 |
LoOP | 40 | 0.38462 | 0.37662 | 0.23895 | 0.22906 | 0.38710 | 0.37913 | 0.96708 |
LDOF | 9 | 0.30769 | 0.29869 | 0.11227 | 0.10073 | 0.32000 | 0.31116 | 0.61492 |
LDOF | 47 | 0.23077 | 0.22077 | 0.27372 | 0.26428 | 0.47059 | 0.46371 | 0.97569 |
LDOF | 50 | 0.30769 | 0.29869 | 0.26242 | 0.25283 | 0.44444 | 0.43722 | 0.97654 |
ODIN | 42 | 0.23077 | 0.22077 | 0.32825 | 0.31952 | 0.52941 | 0.52329 | 0.97231 |
ODIN | 53 | 0.30769 | 0.29869 | 0.31138 | 0.30243 | 0.58065 | 0.57519 | 0.95035 |
ODIN | 84 | 0.38462 | 0.37662 | 0.24988 | 0.24012 | 0.46667 | 0.45973 | 0.91431 |
FastABOD | 3 | 0.15385 | 0.14285 | 0.09311 | 0.08132 | 0.22222 | 0.21211 | 0.63369 |
FastABOD | 24 | 0.15385 | 0.14285 | 0.12289 | 0.11148 | 0.25000 | 0.24025 | 0.58554 |
FastABOD | 75 | 0.23077 | 0.22077 | 0.13087 | 0.11957 | 0.25000 | 0.24025 | 0.57515 |
FastABOD | 100 | 0.23077 | 0.22077 | 0.13130 | 0.12001 | 0.25000 | 0.24025 | 0.57523 |
KDEOS | 37 | 0.15385 | 0.14285 | 0.07461 | 0.06258 | 0.17143 | 0.16066 | 0.87377 |
KDEOS | 54 | 0.07692 | 0.06492 | 0.11805 | 0.10658 | 0.25000 | 0.24025 | 0.92038 |
KDEOS | 56 | 0.07692 | 0.06492 | 0.11195 | 0.10040 | 0.27451 | 0.26508 | 0.92369 |
KDEOS | 64 | 0.07692 | 0.06492 | 0.11716 | 0.10568 | 0.27451 | 0.26508 | 0.93808 |
LDF | 11 | 0.53846 | 0.53246 | 0.36762 | 0.35940 | 0.62069 | 0.61576 | 0.98000 |
LDF | 15 | 0.53846 | 0.53246 | 0.42882 | 0.42139 | 0.64706 | 0.64247 | 0.98731 |
INFLO | 3 | 0.30769 | 0.29869 | 0.10993 | 0.09836 | 0.30769 | 0.29869 | 0.58492 |
INFLO | 20 | 0.30769 | 0.29869 | 0.28063 | 0.27128 | 0.41379 | 0.40617 | 0.97038 |
INFLO | 21 | 0.30769 | 0.29869 | 0.28103 | 0.27169 | 0.42857 | 0.42114 | 0.97008 |
COF | 2 | 0.23077 | 0.22077 | 0.10520 | 0.09357 | 0.27273 | 0.26327 | 0.61142 |
COF | 6 | 0.15385 | 0.14285 | 0.10783 | 0.09624 | 0.27586 | 0.26645 | 0.60577 |
COF | 22 | 0.15385 | 0.14285 | 0.18899 | 0.17844 | 0.25000 | 0.24025 | 0.94808 |