Trade-off between accuracy and fairness of data-driven building and indoor environment models: A comparative study of pre-processing methods

Energy9.00
Volume: 239, Pages: 122273 - 122273
Published: Jan 1, 2022
Abstract
Data-driven models have drawn extensive attention in the building domain in recent years, and their predictive accuracy depends on features or data distribution. Accuracy variation among users or periods creates a certain unfairness to some users. This paper addresses a new research problem called fairness-aware prediction of data-driven building and indoor environment models. First, three types of fairness definitions are introduced in building...
Paper Details
Title
Trade-off between accuracy and fairness of data-driven building and indoor environment models: A comparative study of pre-processing methods
Published Date
Jan 1, 2022
Journal
Volume
239
Pages
122273 - 122273
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