Outputs (4)

Predicting Healthy Start Scheme Uptake using Deprivation and Food Insecurity Measures (2024)
Presentation / Conference Contribution
Makokoro, K., Long, G., Harvey, J., Smith, A., Welham, S., Mansilla, R., Lukinova, E., & Goulding, J. (2024, May). Predicting Healthy Start Scheme Uptake using Deprivation and Food Insecurity Measures. Presented at 2nd Digital Footprints Conference: Linking Digital Data for Social Impact, Bristol, UK

Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake (2023)
Presentation / Conference Contribution
Harvey, J., Long, G., Welham, S., Mansilla, R., Rose, P., Thomas, M., …Goulding, J. (2023). Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake. In Proceedings: 2023 IEEE International Conference on Big Data (BigData) (4530-4538). https://doi.org/10.1109/BigData59044.2023.10386220

Anthocyanins are a class of polyphenols that have received widespread recent attention due to their potential health benefits. However, estimating the dietary intake of anthocyanins at a population level is a challenging task, due to the difficulty o... Read More about Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake.

Bundle entropy as an optimized measure of consumers' systematic product choice combinations in mass transactional data (2022)
Presentation / Conference Contribution
Mansilla, R., Smith, G., Smith, A., & Goulding, J. (2022). Bundle entropy as an optimized measure of consumers' systematic product choice combinations in mass transactional data. In Proceedings 2022 IEEE International Conference on Big Data (1044-1053). https://doi.org/10.1109/BigData55660.2022.10021062

Understanding and measuring the predictability of consumer purchasing (basket) behaviour is of significant value. While predictability measures such as entropy have been well studied and leveraged in other sectors, their development and application t... Read More about Bundle entropy as an optimized measure of consumers' systematic product choice combinations in mass transactional data.

Model Class Reliance for Random Forests (2020)
Presentation / Conference Contribution
Smith, G., Mansilla Lobos, R., & Goulding, J. (2020). Model Class Reliance for Random Forests. In Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020)

Variable Importance (VI) has traditionally been cast as the process of estimating each variable's contribution to a predictive model's overall performance. Analysis of a single model instance, however, guarantees no insight into a variables relevance... Read More about Model Class Reliance for Random Forests.