Classification algorithms Framework (CaF) to Enable Intelligent Systems Using JetBrains MPS Domain-Specific Languages Environment
Authors: Meacham, S., Pech, V. and Nauck, D.
Journal: IEEE Access
Volume: 8
Pages: 14832-14840
eISSN: 2169-3536
DOI: 10.1109/aCCESS.2020.2966630
Abstract:This paper describes the design and development of a Classification algorithms Framework (CaF) using the JetBrains MPS domain-specific languages (DSLs) development environment. It is increasingly recognized that the systems of the future will contain some form of adaptivity therefore making them intelligent systems as opposed to the static systems of the past. These intelligent systems can be extremely complex and difficult to maintain. Descriptions at higher-level of abstraction (system-level) have long been identified by industry and academia to reduce complexity. This research presents a Framework of Classification algorithms at system-level that enables quick experimentation with several different algorithms from Naive Bayes to Logistic Regression. It has been developed as a tool to address the requirements of British Telecom's (BT's) data-science team. The tool has been presented at BT and JetBrains MPS and feedback has been collected and evaluated. Beyond the reduction in complexity through the system-level description, the most prominent advantage of this research is its potential applicability to many application contexts. It has been designed to be applicable for intelligent applications in several domains from business analytics, eLearning to eHealth, etc. Its wide applicability will contribute to enabling the larger vision of artificial Intelligence (aI) adoption in context.
https://eprints.bournemouth.ac.uk/33284/
Source: Scopus
Classification Algorithms Framework (CAF) to Enable Intelligent Systems Using JetBrains MPS Domain-Specific Languages Environment
Authors: Meacham, S., Pech, V. and Nauck, D.
Journal: IEEE ACCESS
Volume: 8
Pages: 14832-14840
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2020.2966630
https://eprints.bournemouth.ac.uk/33284/
Source: Web of Science (Lite)
Classification Algorithms Framework (CAF) to Enable Intelligent Systems Using JetBrains MPS Domain-Specific Languages Environment
Authors: Meacham, S., Pech, V. and Nauck, D.
Journal: IEEE Access
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
ISSN: 2169-3536
Abstract:This paper describes the design and development of a Classification Algorithms Framework (CAF) using the JetBrains MPS domain-specific languages (DSLs) development environment. It is increasingly recognized that the systems of the future will contain some form of adaptivity therefore making them intelligent systems as opposed to the static systems of the past. These intelligent systems can be extremely complex and difficult to maintain. Descriptions at higher-level of abstraction (system-level) have long been identified by industry and academia to reduce complexity. This research presents a Framework of Classification Algorithms at system-level that enables quick experimentation with several different algorithms from Naive Bayes to Logistic Regression. It has been developed as a tool to address the requirements of British Telecom’s (BT’s) data-science team. The tool has been presented at BT and JetBrains MPS and feedback has been collected and evaluated. Beyond the reduction in complexity through the system-level description, the most prominent advantage of this research is its potential applicability to many application contexts. It has been designed to be applicable for intelligent applications in several domains from business analytics, eLearning to eHealth, etc. Its wide applicability will contribute to enabling the larger vision of Artificial Intelligence (AI) adoption in context.
https://eprints.bournemouth.ac.uk/33284/
Source: Manual
Classification Algorithms Framework (CAF) to Enable Intelligent Systems Using JetBrains MPS Domain-Specific Languages Environment.
Authors: Meacham, S., Pech, V. and Nauck, D.D.
Journal: IEEE Access
Volume: 8
Pages: 14832-14840
https://eprints.bournemouth.ac.uk/33284/
Source: DBLP
Classification Algorithms Framework (CAF) to enable Intelligent Systems using JetBrains MPS domain-specific languages environment
Authors: Meacham, S., Pech, V. and Nauck, D.
Journal: IEEE Access
Volume: 8
Pages: 14832-14840
ISSN: 2169-3536
Abstract:This paper describes the design and development of a Classification Algorithms Framework (CAF) using the JetBrains MPS domain-specific languages (DSLs) development environment. It is increasingly recognized that the systems of the future will contain some form of adaptivity therefore making them intelligent systems as opposed to the static systems of the past. These intelligent systems can be extremely complex and difficult to maintain. Descriptions at higher-level of abstraction (system-level) have long been identified by industry and academia to reduce complexity. This research presents a Framework of Classification Algorithms at system-level that enables quick experimentation with several different algorithms from Naive Bayes to Logistic Regression. It has been developed as a tool to address the requirements of British Telecom’s (BT’s) data-science team. The tool has been presented at BT and JetBrains MPS and feedback has been collected and evaluated. Beyond the reduction in complexity through the system-level description, the most prominent advantage of this research is its potential applicability to many application contexts. It has been designed to be applicable for intelligent applications in several domains from business analytics, eLearning to eHealth, etc. Its wide applicability will contribute to enabling the larger vision of Artificial Intelligence (AI) adoption in context.
https://eprints.bournemouth.ac.uk/33284/
Source: BURO EPrints