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》 资源 》论文》the role of textualisation and argumentation in understanding the machine learning process

the role of textualisation and argumentation in understanding the machine learning process

2019-11-04 | |  74 |   41 |   0
Abstract Understanding data, models and predictions is important for machine learning applications. Due to the limitations of our spatial perception and intuition, analysing high-dimensional data is inherently difficult. Furthermore, black-box models achieving high predictive accuracy are widely used, yet the logic behind their predictions is often opaque. Use of textualisation – a natural language narrative of selected phenomena – can tackle these shortcomings. When extended with argumentation theory we could envisage machine learning models and predictions arguing persuasively for their choices.

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