Missing feature re-representation method and system based on graph convolutional network
A convolutional network, network technology
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[0035] When the inventor was conducting research on missing features, he found that the processing methods for missing data in the prior art ignored the correlation between samples of missing data and other samples. After research, the inventor found that the collected samples of original data The correlation between them makes the problem of missing data features can be solved by making full use of the information of other samples to re-express the missing data.
[0036] The present invention proposes a method for re-representing missing features based on a graph convolutional network. The method proposed by the present invention includes two stages: the construction of the graph network and the training of the graph network. In the construction phase of the graph network: firstly, a graph network is constructed by extracting features from the original data set of the machine learning task, and each sample in the original data set is used as a node in the graph network, and t...
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