Feature network methods for machine learning
We develop a graph structure for feature vectors in machine learning, which we denote as a feature network (FN); this is different from sample-based networks, in which nodes simply represent samples. FNs reveal the underlying relationship among feature vector components and re-represent features as...
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| Language: | en_US |
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2021
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| Online Access: | https://hdl.handle.net/2144/42062 |