Improving binary classification using filtering based on k-NN proximity graphs
Abstract One of the ways of increasing recognition ability in classification problem is removing outlier entries as well as redundant and unnecessary features from training set. Filtering and feature selection can have large impact on classifier accuracy and area under the curve (AUC), as noisy data...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2020-03-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s40537-020-00297-7 |