Evaluating Anomaly Detection Algorithms in Power Consumption Data
The quality of data is an important aspect when performing data scientific tasks.Having a clean ground truth dataset is critical to be able to derive analytical resultsfrom experiments. In this thesis, an automated method of checking the correctness of new data against adefined ground truth dataset...
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| Format: | Others |
| Language: | English |
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Uppsala universitet, Institutionen för informationsteknologi
2017
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-328624 |