[2210.12746] Principal Component Classification
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Computer Science > Machine Learning

arXiv:2210.12746 (cs)
[Submitted on 23 Oct 2022 (v1), last revised 26 Oct 2022 (this version, v2)]

Title:Principal Component Classification

Authors:Rozenn Dahyot
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Abstract:We propose to directly compute classification estimates by learning features encoded with their class scores using PCA. Our resulting model has a encoder-decoder structure suitable for supervised learning, it is computationally efficient and performs well for classification on several datasets.
Comments: 5 pages; 5 figures; 1 table
Subjects: Machine Learning (cs.LG); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (stat.ML)
Cite as: arXiv:2210.12746 [cs.LG]
  (or arXiv:2210.12746v2 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2210.12746

Submission history

From: Rozenn Dahyot [view email]
[v1] Sun, 23 Oct 2022 15:05:14 UTC (583 KB)
[v2] Wed, 26 Oct 2022 17:23:29 UTC (583 KB)
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