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Article overview
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How to get the most out of Twinned Regression Methods | Sebastian J. Wetzel
; | Date: |
3 Jan 2023 | Abstract: | Twinned regression methods are designed to solve the dual problem to the
original regression problem, predicting differences between regression targets
rather then the targets themselves. A solution to the original regression
problem can be obtained by ensembling predicted differences between the targets
of an unknown data point and multiple known anchor data points. We explore
different aspects of twinned regression methods: (1) We decompose different
steps in twinned regression algorithms and examine their contributions to the
final performance, (2) We examine the intrinsic ensemble quality, (3) We
combine twin neural network regression with k-nearest neighbor regression to
design a more accurate and efficient regression method, and (4) we develop a
simplified semi-supervised regression scheme. | Source: | arXiv, 2301.01383 | Services: | Forum | Review | PDF | Favorites |
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