A systematic literature review on support vector machines applied to regression

Daniel Mavilo Calderon Nieto, Erik Alex Papa Quiroz, Miguel Ángel Cano Lengua

202114 citationsDOI

Abstract

This article aims to identify the current state of the art of the latest research related to models and algorithms in support vector machines for regression. For that, we use the methodology proposed by Kitchenham and Charter, in order to answer the following research questions: Q1: In which research areas is the support vector machine for regression most used? Q2. What optimization models are used to support vector machine for regression? Q3. What algorithms or optimization methods are used to solve support vector machine for regression? Q4. What nonconvex optimization models use support vector machine for regression? Q5. What optimization algorithms are used for nonconvex models to support vector machine for regression? We obtain valuable information about the questions to construct new models and algorithms in this research area.

Topics & Concepts

Support vector machineRelevance vector machineComputer scienceMachine learningLeast squares support vector machineConstruct (python library)Regression analysisRegressionStructured support vector machineArtificial intelligenceData miningProper linear modelPolynomial regressionMathematicsStatisticsProgramming languageFace and Expression RecognitionData Stream Mining TechniquesMachine Learning and ELM