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A Novel Approach to Semi-Supervised Statistical Machine Learning. Recent successes in the construction of classifiers for making diagnoses and predictions are due in part to their using much data labelled with respect to their class of origin. But typically there are little labelled data but plentiful unlabelled data. The goal of semi-supervised learning (SSL) is to leverage large amounts of unlabelled data to improve the performance using only small labelled datasets and so SSL is of paramount ....A Novel Approach to Semi-Supervised Statistical Machine Learning. Recent successes in the construction of classifiers for making diagnoses and predictions are due in part to their using much data labelled with respect to their class of origin. But typically there are little labelled data but plentiful unlabelled data. The goal of semi-supervised learning (SSL) is to leverage large amounts of unlabelled data to improve the performance using only small labelled datasets and so SSL is of paramount importance to applications where it is expensive or impractical to obtain much labelled data. The project is to develop a novel SSL approach that adopts a missingness mechanism for the missing labels to build a classifier that not only improves accuracy but it can be greater than if the missing labels were known.
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Discovery Early Career Researcher Award - Grant ID: DE240100014
Funder
Australian Research Council
Funding Amount
$424,237.00
Summary
Causal relationship between taste and smell perception and eating behaviour. Around half of all Australians have a poor diet, which is a leading cause of many chronic conditions costing over $70 billion annually. This project aims to develop and apply novel statistical methods for determining the genetic basis of human taste and smell perception and its causal effects on eating behaviour. Expected outcomes include delivering new insights into such underlying individual differences for a wide ran ....Causal relationship between taste and smell perception and eating behaviour. Around half of all Australians have a poor diet, which is a leading cause of many chronic conditions costing over $70 billion annually. This project aims to develop and apply novel statistical methods for determining the genetic basis of human taste and smell perception and its causal effects on eating behaviour. Expected outcomes include delivering new insights into such underlying individual differences for a wide range of taste and olfactory traits; advanced analytical methods to assess causality; and a causal network of these sensory traits across over 100 consumable food items. From these outcomes, the benefits will be new strategies for improving food flavours and eating behaviours to enhance agri-food industry growth.Read moreRead less