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Local Model-Agnostic Explanations for Machine Learning and Time-series Forecasting Models

thesis
posted on 12.01.2022, 03:52 by Rajapaksha Hewa Ranasinghage Dilini Sewwandi
As we rely more and more on Artificial Intelligence machine learning models for real-life decision-making, understanding and trusting the predictions becomes ever more critical. Imagine that when you buy your first home, the bank rejects your mortgage application without any reason. It is practically unethical to make decisions based on automated systems without providing explanations. This refers, how crucial it is to know how and why the system arrived at a conclusion. This is where my Ph.D. comes into play. In my Ph.D. I developed novel algorithms which provide human-understandable explanations for the decisions of classification and forecasting models.

History

Campus location

Australia

Principal supervisor

Christoph Bergmeir

Additional supervisor 1

Wray Buntine

Year of Award

2022

Department, School or Centre

Data Science & Artificial Intelligence

Course

Doctor of Philosophy

Degree Type

DOCTORATE

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