A Novel Minimization Approximation Cost Classification Method to Minimize Misclassification Rate for Dichotomous and Homogeneous Classes-Reference-Cited by-同舟云学术

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A Novel Minimization Approximation Cost Classification Method to Minimize Misclassification Rate for Dichotomous and Homogeneous Classes

Published:2021-01-01 Issue:1 Volume:8 Page:
ISSN:2765-8449
Container-title:RMS: Research in Mathematics & Statistics
language:en
Short-container-title:RMS: Research in Mathematics & Statistics

Author:

Al-Shukeili Mubarak¹,Wesonga Ronald¹²

Affiliation:

1. Department of Statistics, Sultan Qaboos University, Muscat, Oman

2. Data Science Analytics Lab, Department of Statistics, Sultan Qaboos University, Muscat, Oman

Funder

research

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/27658449.2021.2021627

Reference23 articles.

1. The maximal data piling direction for discrimination

2. Optimal cut-off for rare events and unbalanced misclassification costs

3. Influence of observations on the misclassification probability in quadratic discriminant analysis

4. Multilevel multinomial logistic regression model for identifying factors associated with anemia in children 6–59 months in northeastern states of India

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Modifying linearly non-separable support vector machine binary classifier to account for the centroid mean vector;Communications for Statistical Applications and Methods;2023-05-31

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