WBC (version#03)

This dataset consists of examples of different cancer types, benign or malignant. Examples of benign cancer are considered inliers, examples of malignant cancer are considered outliers. After downsampling the outliers, following Schubert et al. [1], 10 outliers remain. 234 instances are duplicates (231 inliers and 3 outliers), therefore 229 outliers were removed from the data set with duplicates and 226 outliers from the dataset without duplicates. Furthermore, we removed 16 instances with missing values, two of them being outliers and 14 inliers. The processed data set has 9 numeric attributes and 454 instances, namely 10 outliers (2.2%) and 444 inliers (97.8%). The same pre-processing has also been applied in [2] and [3].

References:

[1] E. Schubert, R. Wojdanowski, A. Zimek, and H.-P. Kriegel. On evaluation of outlier rankings and outlier scores. In Proc. SDM, pages 1047-1058, 2012.
[2] A. Zimek, M. Gaudet, R. J. G. B. Campello, and J. Sander. Subsampling for efficient and effective unsupervised outlier detection ensembles. In Proc. KDD, pages 428-436, 2013.
[3] H.-P. Kriegel, P. Kroeger, E. Schubert, and A. Zimek. Interpreting and unifying outlier scores. In Proc. SDM, pages 13-24, 2011.

Download all data set variants used (57.1 kB). You can also access the original data. (breast-cancer-wisconsin.data)

Normalized, without duplicates
Normalized, duplicates
Not normalized, without duplicates
Not normalized, duplicates

Normalized, without duplicates

This version contains 9 attributes, 223 objects, 10 outliers (4.48%)

Download raw algorithm results (1.6 MB) Download raw algorithm evaluation table (33.4 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	1	0.90000	0.89531	0.93846	0.93557	0.94737	0.94490	0.99249
KNN	20	0.90000	0.89531	0.96250	0.96074	0.94737	0.94490	0.99718
KNNW	2	0.90000	0.89531	0.92846	0.92510	0.90000	0.89531	0.99202
KNNW	3	0.90000	0.89531	0.93846	0.93557	0.94737	0.94490	0.99249
KNNW	48	0.90000	0.89531	0.96250	0.96074	0.94737	0.94490	0.99718
LOF	57	0.90000	0.89531	0.83806	0.83045	0.90000	0.89531	0.99155
LOF	78	0.90000	0.89531	0.94762	0.94516	0.94737	0.94490	0.99484
LOF	98	0.90000	0.89531	0.95882	0.95689	0.94737	0.94490	0.99671
SimplifiedLOF	84	0.90000	0.89531	0.89558	0.89068	0.90000	0.89531	0.99202
SimplifiedLOF	98	0.90000	0.89531	0.92651	0.92306	0.90000	0.89531	0.99390
LoOP	69	0.40000	0.37183	0.42699	0.40009	0.69231	0.67786	0.96432
LoOP	96	0.50000	0.47653	0.61099	0.59273	0.66667	0.65102	0.97653
LoOP	100	0.50000	0.47653	0.63736	0.62034	0.66667	0.65102	0.97840
LDOF	87	0.40000	0.37183	0.36799	0.33832	0.56000	0.53934	0.95446
LDOF	97	0.40000	0.37183	0.40923	0.38150	0.61538	0.59733	0.95869
LDOF	98	0.40000	0.37183	0.41518	0.38772	0.61538	0.59733	0.96197
ODIN	99	0.48000	0.45559	0.42418	0.39714	0.60000	0.58122	0.96854
ODIN	100	0.48000	0.45559	0.42655	0.39962	0.62069	0.60288	0.96878
FastABOD	6	0.90000	0.89531	0.74877	0.73697	0.90000	0.89531	0.98920
FastABOD	7	0.90000	0.89531	0.94348	0.94082	0.94737	0.94490	0.99390
FastABOD	35	0.90000	0.89531	0.94762	0.94516	0.94737	0.94490	0.99484
KDEOS	2	0.00000	-0.04695	0.04344	-0.00146	0.09783	0.05547	0.43169
KDEOS	14	0.00000	-0.04695	0.07727	0.03395	0.15686	0.11728	0.66338
KDEOS	22	0.00000	-0.04695	0.07579	0.03240	0.21053	0.17346	0.63521
LDF	31	0.90000	0.89531	0.75256	0.74094	0.90000	0.89531	0.99014
LDF	49	0.90000	0.89531	0.95556	0.95347	0.94737	0.94490	0.99624
LDF	77	0.90000	0.89531	0.96250	0.96074	0.94737	0.94490	0.99718
INFLO	97	0.80000	0.79061	0.88598	0.88063	0.81818	0.80965	0.99108
INFLO	98	0.80000	0.79061	0.89012	0.88496	0.81818	0.80965	0.99202
INFLO	99	0.70000	0.68592	0.89535	0.89043	0.82353	0.81524	0.99202
COF	66	0.80000	0.79061	0.81364	0.80489	0.85714	0.85044	0.99061
COF	93	0.70000	0.68592	0.83153	0.82362	0.83333	0.82551	0.99155
COF	97	0.80000	0.79061	0.85083	0.84383	0.80000	0.79061	0.99061

Plots

Precision at n

Adjusted precision at n

Average precision

Adjusted average precision

Maximum F1 score

Adjusted maximum F1 score

ROC AUC

Diversity

A: KNN, B: KNNW, C: LOF, D: SimplifiedLOF, E: LoOP, F: LDOF
G: ODIN, H: KDEOS, I: COF, J: FastABOD, K: LDF, L: INFLO

Normalized, duplicates

This version contains 9 attributes, 454 objects, 10 outliers (2.20%)

Download raw algorithm results (1.9 MB) Download raw algorithm evaluation table (38.8 kB)

Best Parameters

Algorithm	k	P@n	Adj. P@n	AP	Adj. AP	Max-F1	Adj. MF1	ROC AUC
KNN	1	0.90000	0.89775	0.94545	0.94423	0.94737	0.94618	0.99741
KNN	4	0.90000	0.89775	0.95556	0.95455	0.94737	0.94618	0.99820
KNNW	2	0.90000	0.89775	0.94545	0.94423	0.94737	0.94618	0.99730
KNNW	72	0.90000	0.89775	0.95556	0.95455	0.94737	0.94618	0.99820
LOF	100	0.80000	0.79550	0.86016	0.85701	0.81818	0.81409	0.99505
SimplifiedLOF	79	0.50000	0.48874	0.37084	0.35667	0.56000	0.55009	0.97815
SimplifiedLOF	94	0.50000	0.48874	0.56281	0.55297	0.66667	0.65916	0.98716
SimplifiedLOF	98	0.50000	0.48874	0.56283	0.55299	0.69231	0.68538	0.98694
SimplifiedLOF	99	0.50000	0.48874	0.56738	0.55763	0.69231	0.68538	0.98716
LoOP	83	0.30000	0.28423	0.29124	0.27528	0.47368	0.46183	0.97027
LoOP	100	0.30000	0.28423	0.37487	0.36079	0.64286	0.63481	0.97995
LDOF	96	0.30000	0.28423	0.25758	0.24086	0.40909	0.39578	0.96126
LDOF	100	0.30000	0.28423	0.27836	0.26210	0.45161	0.43926	0.96577
ODIN	82	0.40000	0.38649	0.32861	0.31349	0.50000	0.48874	0.97331
ODIN	87	0.40000	0.38649	0.35442	0.33988	0.53333	0.52282	0.97568
ODIN	93	0.36667	0.35240	0.34232	0.32751	0.53333	0.52282	0.97635
FastABOD	28	0.90000	0.89775	0.93704	0.93562	0.94737	0.94618	0.99617
FastABOD	39	0.90000	0.89775	0.93846	0.93708	0.94737	0.94618	0.99640
KDEOS	6	0.20000	0.18198	0.12482	0.10511	0.30769	0.29210	0.86329
KDEOS	7	0.10000	0.07973	0.14225	0.12293	0.32000	0.30468	0.89009
LDF	88	0.90000	0.89775	0.93167	0.93013	0.90000	0.89775	0.99662
LDF	92	0.90000	0.89775	0.93846	0.93708	0.94737	0.94618	0.99640
LDF	94	0.90000	0.89775	0.94545	0.94423	0.94737	0.94618	0.99730
INFLO	78	0.50000	0.48874	0.43972	0.42710	0.69231	0.68538	0.98514
INFLO	95	0.50000	0.48874	0.64361	0.63558	0.72000	0.71369	0.98986
INFLO	99	0.50000	0.48874	0.67200	0.66461	0.72000	0.71369	0.99009
COF	90	0.30000	0.28423	0.38268	0.36877	0.62500	0.61655	0.98198
COF	98	0.50000	0.48874	0.46040	0.44824	0.61538	0.60672	0.98514

Plots

Precision at n

Adjusted precision at n

Average precision

Adjusted average precision

Maximum F1 score

Adjusted maximum F1 score

ROC AUC

Diversity

A: KNN, B: KNNW, C: LOF, D: SimplifiedLOF, E: LoOP, F: LDOF
G: ODIN, H: KDEOS, I: COF, J: FastABOD, K: LDF, L: INFLO

Not normalized, without duplicates

This version contains 9 attributes, 223 objects, 10 outliers (4.48%)

Download raw algorithm results (1.6 MB) Download raw algorithm evaluation table (33.3 kB)

Best Parameters

Algorithm	k	P@n	Adj. P@n	AP	Adj. AP	Max-F1	Adj. MF1	ROC AUC
KNN	1	0.90000	0.89531	0.93846	0.93557	0.94737	0.94490	0.99249
KNN	79	0.90000	0.89531	0.96667	0.96510	0.94737	0.94490	0.99765
KNNW	2	0.90000	0.89531	0.92846	0.92510	0.90000	0.89531	0.99202
KNNW	3	0.90000	0.89531	0.94000	0.93718	0.94737	0.94490	0.99296
KNNW	39	0.90000	0.89531	0.96250	0.96074	0.94737	0.94490	0.99718
LOF	61	0.90000	0.89531	0.94762	0.94516	0.94737	0.94490	0.99484
LOF	98	0.90000	0.89531	0.96250	0.96074	0.94737	0.94490	0.99718
SimplifiedLOF	88	0.90000	0.89531	0.92434	0.92079	0.90000	0.89531	0.99343
SimplifiedLOF	95	0.90000	0.89531	0.94545	0.94289	0.94737	0.94490	0.99437
SimplifiedLOF	100	0.90000	0.89531	0.95000	0.94765	0.94737	0.94490	0.99531
LoOP	95	0.50000	0.47653	0.68037	0.66536	0.75000	0.73826	0.97981
LoOP	98	0.60000	0.58122	0.70380	0.68989	0.75000	0.73826	0.98122
LoOP	100	0.60000	0.58122	0.72166	0.70859	0.75000	0.73826	0.98263
LDOF	89	0.40000	0.37183	0.45022	0.42441	0.59259	0.57347	0.95775
LDOF	98	0.40000	0.37183	0.48601	0.46188	0.64286	0.62609	0.96667
LDOF	100	0.40000	0.37183	0.48447	0.46026	0.66667	0.65102	0.96620
ODIN	100	0.45000	0.42418	0.40953	0.38181	0.62069	0.60288	0.96737
FastABOD	5	0.90000	0.89531	0.74414	0.73213	0.90000	0.89531	0.98779
FastABOD	6	0.90000	0.89531	0.94000	0.93718	0.94737	0.94490	0.99296
FastABOD	61	0.90000	0.89531	0.94762	0.94516	0.94737	0.94490	0.99484
KDEOS	5	0.00000	-0.04695	0.07758	0.03427	0.15385	0.11412	0.65258
KDEOS	11	0.10000	0.05775	0.07706	0.03373	0.14815	0.10816	0.61690
KDEOS	23	0.00000	-0.04695	0.08001	0.03682	0.19512	0.15733	0.63803
LDF	29	0.90000	0.89531	0.89558	0.89068	0.90000	0.89531	0.99202
LDF	35	0.90000	0.89531	0.94762	0.94516	0.94737	0.94490	0.99484
LDF	77	0.90000	0.89531	0.96667	0.96510	0.94737	0.94490	0.99765
INFLO	94	0.80000	0.79061	0.89685	0.89201	0.82353	0.81524	0.99202
INFLO	97	0.80000	0.79061	0.91833	0.91449	0.85714	0.85044	0.99343
COF	66	0.80000	0.79061	0.78155	0.77130	0.80000	0.79061	0.98685
COF	74	0.80000	0.79061	0.90763	0.90330	0.82353	0.81524	0.99343
COF	86	0.80000	0.79061	0.89488	0.88995	0.81818	0.80965	0.99437
COF	93	0.70000	0.68592	0.75422	0.74268	0.83333	0.82551	0.98920

Plots

Precision at n

Adjusted precision at n

Average precision

Adjusted average precision

Maximum F1 score

Adjusted maximum F1 score

ROC AUC

Diversity

A: KNN, B: KNNW, C: LOF, D: SimplifiedLOF, E: LoOP, F: LDOF
G: ODIN, H: KDEOS, I: COF, J: FastABOD, K: LDF, L: INFLO

Not normalized, duplicates

This version contains 9 attributes, 454 objects, 10 outliers (2.20%)

Download raw algorithm results (1.9 MB) Download raw algorithm evaluation table (38.6 kB)

Best Parameters

Algorithm	k	P@n	Adj. P@n	AP	Adj. AP	Max-F1	Adj. MF1	ROC AUC
KNN	1	0.90000	0.89775	0.94545	0.94423	0.94737	0.94618	0.99741
KNN	4	0.90000	0.89775	0.95556	0.95455	0.94737	0.94618	0.99820
KNNW	2	0.90000	0.89775	0.94545	0.94423	0.94737	0.94618	0.99730
KNNW	72	0.90000	0.89775	0.95556	0.95455	0.94737	0.94618	0.99820
LOF	100	0.80000	0.79550	0.85849	0.85530	0.81818	0.81409	0.99482
SimplifiedLOF	79	0.50000	0.48874	0.37084	0.35667	0.56000	0.55009	0.97815
SimplifiedLOF	97	0.50000	0.48874	0.55902	0.54909	0.69231	0.68538	0.98671
SimplifiedLOF	99	0.50000	0.48874	0.56738	0.55763	0.69231	0.68538	0.98716
LoOP	83	0.30000	0.28423	0.29060	0.27462	0.47368	0.46183	0.97005
LoOP	100	0.30000	0.28423	0.37571	0.36165	0.64286	0.63481	0.98018
LDOF	92	0.30000	0.28423	0.23894	0.22180	0.39130	0.37759	0.95676
LDOF	100	0.30000	0.28423	0.27793	0.26167	0.45161	0.43926	0.96554
ODIN	82	0.40000	0.38649	0.32803	0.31289	0.50000	0.48874	0.97309
ODIN	87	0.40000	0.38649	0.35378	0.33922	0.53333	0.52282	0.97556
ODIN	100	0.32500	0.30980	0.33833	0.32343	0.53333	0.52282	0.97590
FastABOD	28	0.90000	0.89775	0.93846	0.93708	0.94737	0.94618	0.99640
FastABOD	75	0.90000	0.89775	0.94000	0.93865	0.94737	0.94618	0.99662
KDEOS	2	0.00000	-0.02252	0.06865	0.04768	0.16000	0.14108	0.71937
KDEOS	7	0.00000	-0.02252	0.04472	0.02320	0.10101	0.08076	0.75293
LDF	88	0.90000	0.89775	0.93167	0.93013	0.90000	0.89775	0.99662
LDF	92	0.90000	0.89775	0.93846	0.93708	0.94737	0.94618	0.99640
LDF	94	0.90000	0.89775	0.94545	0.94423	0.94737	0.94618	0.99730
INFLO	78	0.50000	0.48874	0.43840	0.42575	0.69231	0.68538	0.98491
INFLO	95	0.50000	0.48874	0.64361	0.63558	0.72000	0.71369	0.98986
INFLO	99	0.50000	0.48874	0.67200	0.66461	0.72000	0.71369	0.99009
COF	87	0.40000	0.38649	0.39563	0.38202	0.58065	0.57120	0.98108
COF	90	0.40000	0.38649	0.41073	0.39746	0.64516	0.63717	0.98423
COF	92	0.40000	0.38649	0.43675	0.42406	0.66667	0.65916	0.98423

Plots

Precision at n

Adjusted precision at n

Average precision

Adjusted average precision

Maximum F1 score

Adjusted maximum F1 score

ROC AUC

Diversity

A: KNN, B: KNNW, C: LOF, D: SimplifiedLOF, E: LoOP, F: LDOF
G: ODIN, H: KDEOS, I: COF, J: FastABOD, K: LDF, L: INFLO