Motivated Support Vector Regression using Structural Prior Knowledge

Motivated Support Vector Regression with Structural Prior Knowledge

It’s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Kn...

Knowledge-Based Green’s Kernel for Support Vector Regression

This paper presents a novel prior knowledge-based Green’s kernel for support vector regression SVR . After reviewing the correspondence between support vector kernels used in support vector machines SVMs and regularization operators used in regularization networks and the use of Green’s function of their corresponding regularization operators to construct support vector kernels, a mathematical ...

Support vector regression with random output variable and probabilistic constraints

Support Vector Regression (SVR) solves regression problems based on the concept of Support Vector Machine (SVM). In this paper, a new model of SVR with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. Using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...

Tehran Stock Price Modeling and Forecasting Using Support Vector Regression (SVR) and Its Comparison with the Classic Model ARIMA

Mining Biological Repetitive Sequences Using Support Vector Machines and Fuzzy SVM

Structural repetitive subsequences are most important portion of biological sequences, which play crucial roles on corresponding sequence’s fold and functionality. Biggest class of the repetitive subsequences is “Transposable Elements” which has its own sub-classes upon contexts’ structures. Many researches have been performed to criticality determine the structure and function of repetitiv...