Shuttle (version#06)
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 (8.5 MB) Download raw algorithm evaluation table (45.7 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 | 1 | 0.30769 | 0.29869 | 0.27588 | 0.26646 | 0.51429 | 0.50797 | 0.81535 |
KNN | 3 | 0.23077 | 0.22077 | 0.35849 | 0.35015 | 0.59091 | 0.58559 | 0.98723 |
KNNW | 5 | 0.38462 | 0.37662 | 0.30790 | 0.29890 | 0.45000 | 0.44285 | 0.97923 |
KNNW | 8 | 0.30769 | 0.29869 | 0.32945 | 0.32074 | 0.49057 | 0.48394 | 0.98454 |
KNNW | 10 | 0.30769 | 0.29869 | 0.32718 | 0.31843 | 0.52000 | 0.51376 | 0.98446 |
LOF | 4 | 0.30769 | 0.29869 | 0.11949 | 0.10805 | 0.34783 | 0.33935 | 0.67938 |
LOF | 14 | 0.30769 | 0.29869 | 0.30925 | 0.30027 | 0.52000 | 0.51376 | 0.98569 |
LOF | 16 | 0.23077 | 0.22077 | 0.29744 | 0.28831 | 0.53659 | 0.53056 | 0.98400 |
SimplifiedLOF | 15 | 0.30769 | 0.29869 | 0.26222 | 0.25263 | 0.48148 | 0.47474 | 0.98100 |
SimplifiedLOF | 17 | 0.30769 | 0.29869 | 0.27869 | 0.26931 | 0.52000 | 0.51376 | 0.98292 |
LoOP | 18 | 0.30769 | 0.29869 | 0.22770 | 0.21766 | 0.34483 | 0.33631 | 0.97385 |
LoOP | 33 | 0.23077 | 0.22077 | 0.31482 | 0.30592 | 0.50000 | 0.49350 | 0.98308 |
LDOF | 28 | 0.30769 | 0.29869 | 0.17345 | 0.16271 | 0.33333 | 0.32467 | 0.95185 |
LDOF | 78 | 0.23077 | 0.22077 | 0.29536 | 0.28620 | 0.51282 | 0.50649 | 0.97931 |
LDOF | 83 | 0.23077 | 0.22077 | 0.29747 | 0.28833 | 0.50000 | 0.49350 | 0.98054 |
ODIN | 39 | 0.15385 | 0.14285 | 0.31708 | 0.30820 | 0.57778 | 0.57229 | 0.98512 |
ODIN | 77 | 0.49231 | 0.48571 | 0.38076 | 0.37271 | 0.62069 | 0.61576 | 0.97696 |
ODIN | 82 | 0.61538 | 0.61038 | 0.35530 | 0.34692 | 0.61538 | 0.61038 | 0.96042 |
ODIN | 90 | 0.61538 | 0.61038 | 0.37056 | 0.36237 | 0.64000 | 0.63532 | 0.92858 |
FastABOD | 18 | 0.23077 | 0.22077 | 0.15649 | 0.14552 | 0.23810 | 0.22819 | 0.80285 |
FastABOD | 48 | 0.23077 | 0.22077 | 0.17583 | 0.16512 | 0.28571 | 0.27643 | 0.80792 |
FastABOD | 92 | 0.23077 | 0.22077 | 0.17682 | 0.16611 | 0.28571 | 0.27643 | 0.81162 |
FastABOD | 100 | 0.23077 | 0.22077 | 0.17636 | 0.16565 | 0.28571 | 0.27643 | 0.81223 |
KDEOS | 91 | 0.23077 | 0.22077 | 0.17026 | 0.15948 | 0.30303 | 0.29397 | 0.96000 |
KDEOS | 93 | 0.23077 | 0.22077 | 0.17268 | 0.16193 | 0.28571 | 0.27643 | 0.96092 |
KDEOS | 98 | 0.23077 | 0.22077 | 0.17506 | 0.16434 | 0.30769 | 0.29869 | 0.96062 |
KDEOS | 100 | 0.23077 | 0.22077 | 0.17554 | 0.16482 | 0.30000 | 0.29090 | 0.95869 |
LDF | 5 | 0.15385 | 0.14285 | 0.29716 | 0.28802 | 0.60000 | 0.59480 | 0.97569 |
LDF | 6 | 0.23077 | 0.22077 | 0.27600 | 0.26659 | 0.50000 | 0.49350 | 0.97815 |
LDF | 12 | 0.23077 | 0.22077 | 0.32381 | 0.31502 | 0.56522 | 0.55957 | 0.98708 |
LDF | 13 | 0.23077 | 0.22077 | 0.32583 | 0.31707 | 0.55556 | 0.54978 | 0.98700 |
INFLO | 12 | 0.30769 | 0.29869 | 0.19625 | 0.18580 | 0.36735 | 0.35912 | 0.88438 |
INFLO | 25 | 0.15385 | 0.14285 | 0.27600 | 0.26659 | 0.45283 | 0.44572 | 0.98046 |
INFLO | 26 | 0.15385 | 0.14285 | 0.27798 | 0.26860 | 0.46154 | 0.45454 | 0.98023 |
INFLO | 31 | 0.15385 | 0.14285 | 0.27969 | 0.27033 | 0.45455 | 0.44745 | 0.97962 |
COF | 14 | 0.38462 | 0.37662 | 0.24966 | 0.23991 | 0.41667 | 0.40908 | 0.96654 |
COF | 29 | 0.23077 | 0.22077 | 0.38916 | 0.38122 | 0.61905 | 0.61410 | 0.98815 |
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 (44.9 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 | 0.30769 | 0.29869 | 0.15643 | 0.14546 | 0.30769 | 0.29869 | 0.81369 |
KNN | 7 | 0.23077 | 0.22077 | 0.24029 | 0.23041 | 0.42308 | 0.41558 | 0.97577 |
KNNW | 3 | 0.23077 | 0.22077 | 0.11292 | 0.10139 | 0.24000 | 0.23012 | 0.71404 |
KNNW | 6 | 0.23077 | 0.22077 | 0.15050 | 0.13946 | 0.27586 | 0.26645 | 0.92377 |
KNNW | 12 | 0.23077 | 0.22077 | 0.17997 | 0.16931 | 0.26531 | 0.25576 | 0.96092 |
KNNW | 13 | 0.23077 | 0.22077 | 0.18127 | 0.17062 | 0.26531 | 0.25576 | 0.96062 |
LOF | 9 | 0.30769 | 0.29869 | 0.17780 | 0.16711 | 0.37037 | 0.36219 | 0.93562 |
LOF | 14 | 0.23077 | 0.22077 | 0.22988 | 0.21986 | 0.40909 | 0.40141 | 0.94685 |
LOF | 20 | 0.07692 | 0.06492 | 0.17473 | 0.16400 | 0.36735 | 0.35912 | 0.95915 |
SimplifiedLOF | 2 | 0.23077 | 0.22077 | 0.09322 | 0.08143 | 0.30000 | 0.29090 | 0.62831 |
SimplifiedLOF | 20 | 0.15385 | 0.14285 | 0.19724 | 0.18681 | 0.34483 | 0.33631 | 0.96277 |
SimplifiedLOF | 23 | 0.15385 | 0.14285 | 0.19723 | 0.18679 | 0.30303 | 0.29397 | 0.96500 |
SimplifiedLOF | 99 | 0.07692 | 0.06492 | 0.17670 | 0.16600 | 0.36364 | 0.35536 | 0.95192 |
LoOP | 2 | 0.23077 | 0.22077 | 0.09095 | 0.07913 | 0.30000 | 0.29090 | 0.67438 |
LoOP | 26 | 0.15385 | 0.14285 | 0.19913 | 0.18872 | 0.35294 | 0.34453 | 0.96292 |
LoOP | 28 | 0.23077 | 0.22077 | 0.19930 | 0.18889 | 0.33333 | 0.32467 | 0.96254 |
LoOP | 29 | 0.15385 | 0.14285 | 0.19527 | 0.18481 | 0.32653 | 0.31778 | 0.96331 |
LDOF | 3 | 0.23077 | 0.22077 | 0.08301 | 0.07109 | 0.24000 | 0.23012 | 0.52508 |
LDOF | 39 | 0.23077 | 0.22077 | 0.17512 | 0.16440 | 0.27451 | 0.26508 | 0.95738 |
LDOF | 51 | 0.15385 | 0.14285 | 0.15933 | 0.14841 | 0.30303 | 0.29397 | 0.96031 |
LDOF | 58 | 0.15385 | 0.14285 | 0.15798 | 0.14704 | 0.31746 | 0.30859 | 0.95962 |
ODIN | 45 | 0.20513 | 0.19479 | 0.20069 | 0.19030 | 0.42857 | 0.42114 | 0.95169 |
ODIN | 53 | 0.23077 | 0.22077 | 0.23570 | 0.22576 | 0.47368 | 0.46684 | 0.94665 |
ODIN | 59 | 0.17949 | 0.16882 | 0.23009 | 0.22008 | 0.50000 | 0.49350 | 0.93577 |
ODIN | 68 | 0.25641 | 0.24674 | 0.20753 | 0.19723 | 0.40000 | 0.39220 | 0.92469 |
FastABOD | 3 | 0.15385 | 0.14285 | 0.06284 | 0.05066 | 0.21053 | 0.20026 | 0.62446 |
FastABOD | 69 | 0.15385 | 0.14285 | 0.07675 | 0.06474 | 0.21053 | 0.20026 | 0.57831 |
KDEOS | 86 | 0.07692 | 0.06492 | 0.09656 | 0.08482 | 0.16495 | 0.15409 | 0.91115 |
KDEOS | 87 | 0.15385 | 0.14285 | 0.09836 | 0.08664 | 0.16327 | 0.15239 | 0.91092 |
KDEOS | 97 | 0.15385 | 0.14285 | 0.10726 | 0.09565 | 0.21053 | 0.20026 | 0.90808 |
LDF | 4 | 0.30769 | 0.29869 | 0.12516 | 0.11378 | 0.34483 | 0.33631 | 0.63146 |
LDF | 11 | 0.23077 | 0.22077 | 0.29009 | 0.28086 | 0.54545 | 0.53955 | 0.97546 |
INFLO | 9 | 0.30769 | 0.29869 | 0.11521 | 0.10371 | 0.30769 | 0.29869 | 0.77654 |
INFLO | 19 | 0.23077 | 0.22077 | 0.18701 | 0.17644 | 0.32258 | 0.31377 | 0.94954 |
INFLO | 20 | 0.23077 | 0.22077 | 0.18518 | 0.17459 | 0.33333 | 0.32467 | 0.95438 |
INFLO | 52 | 0.07692 | 0.06492 | 0.16435 | 0.15349 | 0.29032 | 0.28110 | 0.96038 |
COF | 2 | 0.23077 | 0.22077 | 0.07516 | 0.06313 | 0.27273 | 0.26327 | 0.58046 |
COF | 24 | 0.15385 | 0.14285 | 0.15835 | 0.14741 | 0.25316 | 0.24346 | 0.94923 |
COF | 36 | 0.07692 | 0.06492 | 0.15471 | 0.14373 | 0.36000 | 0.35168 | 0.93762 |