Impacts of noise on machine learning
96 p.
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2011
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| Online Access: | http://hdl.handle.net/10356/46776 |
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sg-ntu-dr.10356-467762023-07-04T15:32:22Z Impacts of noise on machine learning Qiao, Kaimu Mao Kezhi School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing 96 p. Noise in real-world data is quite common and may impact the interpretations of the data, classifiers constructed from the data and classification decisions made based on the data. It can decrease the classifier's performance in many aspects such as classification accuracy, time in building a classifier and so on. Handling noise has become a key issue in machine learning and data mining. Many learning algorithms have been modified to enhance their performance in the environment of noise, like robust learners. However, when the noise level goes high, the performance of these algorithms may not be as good as expected. Thus, a better way is to preprocess the data before a classifier is constructed. Conventional mechanisms include noise filter and data polishing. Master of Science (Computer Control and Automation) 2011-12-23T09:51:10Z 2011-12-23T09:51:10Z 2010 2010 Thesis http://hdl.handle.net/10356/46776 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Qiao, Kaimu Impacts of noise on machine learning |
| description |
96 p. |
| author2 |
Mao Kezhi |
| author_facet |
Mao Kezhi Qiao, Kaimu |
| format |
Theses and Dissertations |
| author |
Qiao, Kaimu |
| author_sort |
Qiao, Kaimu |
| title |
Impacts of noise on machine learning |
| title_short |
Impacts of noise on machine learning |
| title_full |
Impacts of noise on machine learning |
| title_fullStr |
Impacts of noise on machine learning |
| title_full_unstemmed |
Impacts of noise on machine learning |
| title_sort |
impacts of noise on machine learning |
| publishDate |
2011 |
| url |
http://hdl.handle.net/10356/46776 |
| _version_ |
1772825679535013888 |