Bruijn, S.F. de (2016) Discovering Features for a Smart Heating System. Master's Thesis / Essay, Computing Science.
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Abstract
When modeling data, the selection of features is important in determining the quality of the model. For this thesis we explore the possibility of discovering new features by clustering the data in different ways. We assess these feature engineering techniques in the context of a smart heating system. A smart heating solution is designed, implemented and deployed in an office building with about 100 offices. Having an accurate model of the office temperature is important when trying to save energy, as the model allows us to predict when we can turn down the heating system. Thus, we assess whether or not we can improve the models we have using these feature engineering techniques. The method of choice for this assessment is a form of cross-validation, where we leave one of the features out from the model creation, and see if we can derive its existence from the data.
Item Type: | Thesis (Master's Thesis / Essay) |
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Degree programme: | Computing Science |
Thesis type: | Master's Thesis / Essay |
Language: | English |
Date Deposited: | 15 Feb 2018 08:25 |
Last Modified: | 15 Feb 2018 08:25 |
URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/14655 |
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