Induced Voronoï Kernels for Principal Manifolds Approximation
We present a new interpolation technique allowing to build an approximation of a priori unknown principal manifolds of a data set which may be non-linear, non-connected and of various intrinsic dimension. This technique is based onto the Induced Delaunay Triangulation of the data built by a Topology Representing Network. It opens the way to a new field of research and applications in data analysis, data modeling and forecasting.
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