https://ogma.newcastle.edu.au/vital/access/ /manager/Index en-au 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38588 th century for which measurements were tabulated, and a governing functional relationship was postulated. Using leave-one-out cross-validation, in training our method ranks first in 350 out of the 352 datasets. Only six machine learning algorithms ranked first in at least one of the 352 datasets on testing; our approach ranked first 192 times, i.e. more all of the other algorithms combined. The results favourably speak about the robustness of our methodology. We conclude that the use of analytic continued fractions in regression deserves further study and we also advocate that Schaffer's data collection should also be included in the repertoire of datasets to test the performance of machine learning and regression algorithms.]]> Mon 20 Nov 2023 14:40:26 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:35259 Fri 05 Jul 2019 12:34:18 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42779 Fri 02 Sep 2022 14:18:56 AEST ]]>