Quadratic Multiform Separation: A New Classification Model in Machine Learning
Machine Learning
2022-08-18 v2 Machine Learning
Abstract
In this paper we present a new classification model in machine learning. Our result is threefold: 1) The model produces comparable predictive accuracy to that of most common classification models. 2) It runs significantly faster than most common classification models. 3) It has the ability to identify a portion of unseen samples for which class labels can be found with much higher predictive accuracy. Currently there are several patents pending on the proposed model.
Cite
@article{arxiv.2110.04925,
title = {Quadratic Multiform Separation: A New Classification Model in Machine Learning},
author = {Ko-Hui Michael Fan and Chih-Chung Chang and Kuang-Hsiao-Yin Kongguoluo},
journal= {arXiv preprint arXiv:2110.04925},
year = {2022}
}