1 citations · 1 across the 4 of their papers we have counts for
5 papers
Analysing Donors' Behaviour in Non-profit Organisations for Disaster Resilience: The 2019--2020 Australian Bushfires Case Study
Dilini Rajapaksha, Kacper Sokol, Jeffrey Chan +3
With the advancement and proliferation of technology, non-profit organisations have embraced social media platforms to improve their operational capabilities through brand advocacy…
LIMREF: Local Interpretable Model Agnostic Rule-based Explanations for Forecasting, with an Application to Electricity Smart Meter Data
Dilini Rajapaksha, Christoph Bergmeir
Accurate electricity demand forecasts play a crucial role in sustainable power systems. To enable better decision-making especially for demand flexibility of the end-user, it is ne…
LoMEF: A Framework to Produce Local Explanations for Global Model Time Series Forecasts
Dilini Rajapaksha, Christoph Bergmeir, Rob J Hyndman
Global Forecasting Models (GFM) that are trained across a set of multiple time series have shown superior results in many forecasting competitions and real-world applications compa…
SQAPlanner: Generating Data-Informed Software Quality Improvement Plans
Dilini Rajapaksha, Chakkrit Tantithamthavorn, Jirayus Jiarpakdee +3
Software Quality Assurance (SQA) planning aims to define proactive plans, such as defining maximum file size, to prevent the occurrence of software defects in future releases. To a…
LoRMIkA: Local rule-based model interpretability with k-optimal associations
Dilini Rajapaksha, Christoph Bergmeir, Wray Buntine
As we rely more and more on machine learning models for real-life decision-making, being able to understand and trust the predictions becomes ever more important. Local explainer m…