Data on Machine Learning Described by Researchers at University of New South Wales (Learning from machines to close the gap between funding and expenditure in the Australian National Disability Insurance Scheme): Machine Learning

2022 MAY 25 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- New research on artificial intelligence is the subject of a new report. According to news reporting originating from Canberra, Australia, by NewsRx correspondents, research stated, “The Australian National Disability Insurance Scheme (NDIS) allocates funds to participants for purchase of services.”

Our news reporters obtained a quote from the research from University of New South Wales: “Only one percent of the 89,299 participants spent all of their allocated funds with 85 participants having failed to spend any, meaning that most of the participants were left with unspent funds. The gap between the allocated budget and realised expenditure reflects misallocation of funds. Thus we employ alternative machine learning techniques to estimate budget and close the gap while maintaining the aggregate level of spending. Three experiments are conducted to test the machine learning models in estimating the budget, expenditure and the resulting gap; compare the learning rate between machines and humans; and identify the significant explanatory variables.”

According to the news editors, the research concluded: “Results show that machines learn ‘faster’ than humans; machine learning models can improve the efficiency of the NDIS implementation; and significant explanatory variables identified by decision tree models and regression analysis are similar.”

For more information on this research see: Learning from machines to close the gap between funding and expenditure in the Australian National Disability Insurance Scheme. International Journal of Information Management Data Insights, 2022,2(1):100077. The publisher for International Journal of Information Management Data Insights is Elsevier.

A free version of this journal article is available at https://doi.org/10.1016/j.jjimei.2022.100077.

Our news journalists report that more information may be obtained by contacting Satish Chand, School of Business, University of New South Wales, Northcott Dr, Campbell, Canberra ACT 2612, Australia. Additional authors for this research include Yu Zhang.

(Our reports deliver fact-based news of research and discoveries from around the world.)