most citedInterpretable Dimensionality Reduction by Feature Preserving Manifold Approximation and Projection

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.CV2022★ 2 cited

Interpretable Dimensionality Reduction by Feature Preserving Manifold Approximation and Projection

Yang Yang, Hongjian Sun, Jialei Gong +1

Nonlinear dimensionality reduction lacks interpretability due to the absence of source features in low-dimensional embedding space. We propose an interpretable method featMAP to pr…