Interval Regression Analysis with Reduced Support Vector Machine
نویسندگان
چکیده
The support vector machine (SVM) has been widely used in pattern recognition, regression and distribution estimation for crisp data. However, when dealing with large-scale data sets, the solution by using SVM with nonlinear kernels may be difficult to find. Under this circumstance, to develop an efficient method is necessary. Recently the reduced support vector machine (RSVM) was proposed as an alternative of the standard SVM. It has been proved more efficient than the traditional SVM in processing large-scaled data. In this paper we introduce the principle of RSVM to evaluate interval regression analysis.
منابع مشابه
Application of Support Vector Machine Regression for Predicting Critical Responses of Flexible Pavements
This paper aims to assess the application of Support Vector Machine (SVM) regression in order to analysis flexible pavements. To this end, 10000 Four-layer flexible pavement sections consisted of asphalt concrete layer, granular base layer, granular subbase layer, and subgrade soil were analyzed under the effect of standard axle loading using multi-layered elastic theory and pavement critical r...
متن کاملSupport 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...
متن کاملComparison of classic regression methods with neural network and support vector machine in classifying groundwater resources
In the present era, classification of data is one of the most important issues in various sciences in order to detect and predict events. In statistics, the traditional view of these classifications will be based on classic methods and statistical models such as logistic regression. In the present era, known as the era of explosion of information, in most cases, we are faced with data that c...
متن کاملLeast-squares support vector machine and its application in the simultaneous quantitative spectrophotometric determination of pharmaceutical ternary mixture
This paper proposes the least-squares support vector machine (LS-SVM) as an intelligent method applied on absorption spectra for the simultaneous determination of paracetamol (PCT), caffeine (CAF) and ibuprofen (IB) in Novafen. The signal to noise ratio (S/N) increased. Also, In the LS - SVM model, Kernel parameter (σ2) and capacity factor (C) were optimized. Excellent prediction was shown usin...
متن کاملSupport Vector Machine for Interval Regression
Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity mode...
متن کامل