Nested Barycentric Coordinate System as an Explicit Feature Map

Published: Feb 5, 2020
Abstract
We propose a new embedding method which is particularly well-suited for settings where the sample size greatly exceeds the ambient dimension. Our technique consists of partitioning the space into simplices and then embedding the data points into features corresponding to the simplices' barycentric coordinates. We then train a linear classifier in the rich feature space obtained from the simplices. The decision boundary may be highly non-linear,...
Paper Details
Title
Nested Barycentric Coordinate System as an Explicit Feature Map
Published Date
Feb 5, 2020
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