GRW-SCMF selects multi-label features by scoring each feature with a random walk-derived association matrix that is further refined by shared low-dimensional feature-label alignment, and it reports improved classification performance on seven datasets.
Feature selection: A data perspective
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Graph Random Walk with Feature-Label Space Alignment: A Multi-Label Feature Selection Method
GRW-SCMF selects multi-label features by scoring each feature with a random walk-derived association matrix that is further refined by shared low-dimensional feature-label alignment, and it reports improved classification performance on seven datasets.