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Aug 15, 2012 · SSCR seeks a sparse signomial function by solving a linear program to minimize the weighted sum of the ℓ 1-norm of the coefficient vector of the ...
The sparse signomial classification and regression model - IDEAS/RePEc
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Kernel-based methods (KBMs) such as support vector machines (SVMs) are popular data mining tools for solving classification and regression problems.
... In this paper, we develop two variable selection methods for nonlinear classification using the signomial classification (SC) method recently proposed by ...
The sparse signomial classification and regression model ; Year of publication: 2014 ; Authors: Lee, Kyungsik ; Kim, Norman ; Jeong, Myong K. ; Published in: Data ...
TL;DR: This work presents the sparse signomial classification and regression (SSCR) model, which employs the signomial function in the original variables and ...
SSCR seeks a sparse signomial function by solving a linear program to minimize the weighted sum of the ℓ 1-norm of the coefficient vector of the function and ...
TITLE: A Sparse Signomial Model for Classification and. Regression. SPEAKER: Professor Myong K. (MK) Jeong. ABSTRACT: Support Vector Machine
Kyungsik Lee, Norman Kim, Myong K. Jeong: The sparse signomial classification and regression model. Ann. Oper. Res. 216(1): 257-286 (2014). [c1]. view.
This work presents the sparse signomial classification and regression (SSCR) model, which employs the signomial function in the original variables and can ...
Norman Kim's 7 research works with 64 citations, including: The sparse signomial classification and regression model.