Principal Component Classification
Machine Learning
2022-10-27 v2 Computer Vision and Pattern Recognition
Machine Learning
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.
Cite
@article{arxiv.2210.12746,
title = {Principal Component Classification},
author = {Rozenn Dahyot},
journal= {arXiv preprint arXiv:2210.12746},
year = {2022}
}
Comments
5 pages; 5 figures; 1 table