https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29578 Wed 17 Nov 2021 16:29:30 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:3002 Wed 11 Apr 2018 17:22:49 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:8461 Sat 24 Mar 2018 08:42:08 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29662 n = 18 886; ELSA, n = 9181; HRS, n = 19 303; and SHARE, n = 29 917. The microdata, along with further details about the harmonization process and all metadata, are available through the World Health Organization (WHO) data archive at [http://apps.who.int/healthinfo/systems/surveydata/index.php/catalog]. Further information and enquiries can be made to [sagesurvey@who.int] or the corresponding author. The data resource will continue to be updated with data across additional waves of these surveys and new waves.]]> Sat 24 Mar 2018 07:32:18 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:16196 Mon 20 Nov 2023 14:25:33 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:40204 k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.]]> Mon 11 Jul 2022 11:13:16 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:41305 Mon 01 Aug 2022 12:23:44 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49686 Fri 02 Jun 2023 12:33:56 AEST ]]>