Support Vector Machines (SVMs) represent a robust and versatile class of machine learning algorithms that have significantly shaped the fields of pattern recognition, classification, and regression.
Abstract: Regression plays an important role in signal processing, identifying and modeling. This paper proposes a regression algorithm based on least squares support vector machine. In the algorithm, ...
The Basel II capital accord encourages banks to develop internal rating models that are financially intuitive, easily interpretable and optimally predictive for default. Standard linear logistic ...
Abstract: Due to the increasing demand for monitoring sea ice thickness (SIT) in the global environment, the SIT inversion based on Global Navigation Satellite System-Reflectometry (GNSS-R) has ...
Figure 5: Three robust error functions which are insensitive to small errors. Left: Logarithm of mixture with two Gaussians with equal variance and different means ...
This paper focuses on feature selection methods for support vector machine (SVM) classifiers, checking their optimality by comparing them with some statistical and baseline methods. To achieve the ...
A novel machine learning-assisted approach for formula optimization, termed UD-SVR, is introduced by combining uniform design with support vector regression. This method was employed to optimize both ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The aim of this study was to analyze the proteomic differences in bone marrow aspirate ...
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