Implicit Multidimensional Projection of Local Subspaces

We propose a visualization method to understand the effect of multidimensional projection on local subspaces, using implicit function differentiation. Here, we subspace as neighborhood data points. Existing methods focus points, and information is ignored. Our able analyze shape directional gain more insights into global structure through perception structures. Local subspaces are fitted by ellipses that spanned basis vectors. An accurate efficient vector transformation proposed based analytical differentiation projections formulated functions. The results visualized glyphs analyzed full set specifically-designed interactions supported in our web-based tool. usefulness demonstrated various multi- high-dimensional benchmark datasets. evaluated numerical comparisons; overall exploration examples use cases.