Soft-SVM Regression For Binary Classification

@article{Huang2022SoftSVMRF,
  title={Soft-SVM Regression For Binary Classification},
  author={Man-Hsin Huang and Luis Carvalho},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.11735}
}
The binomial deviance and the SVM hinge loss functions are two of the most widely used loss functions in machine learning. While there are many similarities between them, they also have their own strengths when dealing with different types of data. In this work, we introduce a new exponential family based on a convex relaxation of the hinge loss function using softness and class-separation parameters. This new family, denoted Soft-SVM, allows us to prescribe a generalized linear model that… 

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