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arXiv · 2110.04925

Quadratic Multiform Separation: A New Classification Model in Machine Learning

Ko-Hui Michael Fan·Chih-Chung Chang·Kuang-Hsiao-Yin Kongguoluo
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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.

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Ko-Hui Michael Fan, Chih-Chung Chang, Kuang-Hsiao-Yin Kongguoluo. 2021-10-10. Quadratic Multiform Separation: A New Classification Model in Machine Learning. https://arxiv.org/abs/2110.04925

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