Ionosphere
This dataset differentiates good radars which show evidence of some kind of structure in the ionosphere, and bad radars for which signals pass through the radar. In this version (HiCS, [1]), the authors use the class b (minority) as outliers and class g as inliers. They removed attributes 1 and 2 from their dataset. Therefore, after the preprocessing, this dataset has 32 numeric attributes and 351 instances, 126 outliers (35.9%) and 225 inliers (64.1%). This database contains only 1 duplicate, so we did not create a version without duplicates.
References:
[1] F. Keller, E. Mueller, and K. Boehm. HiCS: high contrast subspaces for density-based outlier ranking. In Proc. ICDE, 2012.
Download all data set variants used (28.9 kB). You can also access the original data. (real world datasets)
Normalized, without duplicates
This version contains 32 attributes, 351 objects, 126 outliers (35.90%)
Download raw algorithm results (3.1 MB) Download raw algorithm evaluation table (52.7 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 | 0.84921 | 0.76476 | 0.92988 | 0.89061 | 0.87764 | 0.80911 | 0.92737 |
KNNW | 2 | 0.84921 | 0.76476 | 0.92806 | 0.88778 | 0.88235 | 0.81647 | 0.92374 |
KNNW | 4 | 0.85714 | 0.77714 | 0.92961 | 0.89018 | 0.88235 | 0.81647 | 0.92698 |
LOF | 9 | 0.83333 | 0.74000 | 0.86670 | 0.79205 | 0.83665 | 0.74518 | 0.89898 |
LOF | 83 | 0.72222 | 0.56667 | 0.85730 | 0.77739 | 0.75949 | 0.62481 | 0.90427 |
SimplifiedLOF | 9 | 0.80952 | 0.70286 | 0.87282 | 0.80160 | 0.83459 | 0.74195 | 0.90409 |
SimplifiedLOF | 10 | 0.82540 | 0.72762 | 0.87644 | 0.80724 | 0.83333 | 0.74000 | 0.90504 |
SimplifiedLOF | 11 | 0.82540 | 0.72762 | 0.87748 | 0.80887 | 0.82890 | 0.73308 | 0.90416 |
LoOP | 11 | 0.80159 | 0.69048 | 0.86177 | 0.78436 | 0.82090 | 0.72060 | 0.90210 |
LoOP | 12 | 0.80952 | 0.70286 | 0.86116 | 0.78340 | 0.81955 | 0.71850 | 0.89926 |
LoOP | 14 | 0.80159 | 0.69048 | 0.85278 | 0.77034 | 0.82759 | 0.73103 | 0.89291 |
LDOF | 14 | 0.79365 | 0.67810 | 0.84845 | 0.76358 | 0.80755 | 0.69977 | 0.89608 |
LDOF | 15 | 0.80159 | 0.69048 | 0.84828 | 0.76332 | 0.80899 | 0.70202 | 0.89340 |
LDOF | 16 | 0.80159 | 0.69048 | 0.85465 | 0.77325 | 0.82129 | 0.72122 | 0.89295 |
ODIN | 13 | 0.78042 | 0.65746 | 0.84768 | 0.76239 | 0.78088 | 0.65817 | 0.85224 |
ODIN | 18 | 0.79206 | 0.67562 | 0.85499 | 0.77379 | 0.79528 | 0.68063 | 0.84843 |
ODIN | 19 | 0.77438 | 0.64803 | 0.85596 | 0.77530 | 0.78226 | 0.66032 | 0.84616 |
FastABOD | 3 | 0.81746 | 0.71524 | 0.88811 | 0.82546 | 0.82353 | 0.72471 | 0.91333 |
FastABOD | 11 | 0.85714 | 0.77714 | 0.90893 | 0.85793 | 0.85714 | 0.77714 | 0.90808 |
KDEOS | 57 | 0.75397 | 0.61619 | 0.72529 | 0.57145 | 0.76364 | 0.63127 | 0.82748 |
KDEOS | 59 | 0.76984 | 0.64095 | 0.71910 | 0.56180 | 0.77154 | 0.64360 | 0.82790 |
KDEOS | 67 | 0.75397 | 0.61619 | 0.71020 | 0.54792 | 0.79699 | 0.68331 | 0.83242 |
KDEOS | 71 | 0.76190 | 0.62857 | 0.71100 | 0.54916 | 0.78327 | 0.66190 | 0.83400 |
LDF | 3 | 0.82540 | 0.72762 | 0.88445 | 0.81974 | 0.83761 | 0.74667 | 0.90328 |
LDF | 50 | 0.80952 | 0.70286 | 0.88006 | 0.81289 | 0.81890 | 0.71748 | 0.91668 |
INFLO | 9 | 0.80952 | 0.70286 | 0.86613 | 0.79117 | 0.81600 | 0.71296 | 0.90342 |
INFLO | 10 | 0.81746 | 0.71524 | 0.86422 | 0.78819 | 0.82129 | 0.72122 | 0.90379 |
COF | 89 | 0.84921 | 0.76476 | 0.92927 | 0.88967 | 0.84921 | 0.76476 | 0.95425 |
COF | 100 | 0.84921 | 0.76476 | 0.93965 | 0.90585 | 0.85609 | 0.77550 | 0.96032 |