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A COMPREHENSIVE APPROACH TOWARDS DEVELOPING INTELLIGENT SYSTEM: INFORMATION SYSTEM DEVELOPMENT USING DATA ANALYSIS - Softcover
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Designing Intelligent Software System for software defect prediction (SDP) is an important challenge in the field of software engineering using machine learning algorithms as class-imbalance problems cause difficulties for classification of defective and non-defective modules so Imbalanced learning deals with this problem and also used by researchers, but unfortunately with inconsistent results. For this, we conducted a comprehensive experiment for designing intelligent software system using the effect of imbalanced learning on imbalance dataset metrics, type of classifier, input metrics and imbalanced learning method. The major requirement in designing Intelligent Software System for software defect prediction typically uses methods and frameworks which allow software engineers to focus on development activities in terms of defect-prone code, thereby improving software quality and making better use of resources. Many software defect prediction datasets, methods and frameworks are complex, thus a comprehensive picture of defect prediction research from development phase is missing. This research aims to identify and analyse the research trends, datasets, methods and frameworks used in software defect prediction research from 2014 to 2020.
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A COMPREHENSIVE APPROACH TOWARDS DEVELOPING INTELLIGENT SYSTEM
Verlag:
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203202495
ISBN 13: 9786203202496
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Anbieter: moluna, Greven, Deutschland
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Banga ManuManu Banga, Ph.D., M.Tech, B.Tech has research interest in developing intelligent system using data analysis and published several papers in SCI indexed journals.Designing Intelligent Software System for software defect. Bestandsnummer des Verkäufers 452576181
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A COMPREHENSIVE APPROACH TOWARDS DEVELOPING INTELLIGENT SYSTEM
Verlag:
LAP LAMBERT Academic Publishing Feb 2021, 2021
ISBN 10: 6203202495
ISBN 13: 9786203202496
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Designing Intelligent Software System for software defect prediction (SDP) is an important challenge in the field of software engineering using machine learning algorithms as class-imbalance problems cause difficulties for classification of defective and non-defective modules so Imbalanced learning deals with this problem and also used by researchers, but unfortunately with inconsistent results. For this, we conducted a comprehensive experiment for designing intelligent software system using the effect of imbalanced learning on imbalance dataset metrics, type of classifier, input metrics and imbalanced learning method. The major requirement in designing Intelligent Software System for software defect prediction typically uses methods and frameworks which allow software engineers to focus on development activities in terms of defect-prone code, thereby improving software quality and making better use of resources. Many software defect prediction datasets, methods and frameworks are complex, thus a comprehensive picture of defect prediction research from development phase is missing. This research aims to identify and analyse the research trends, datasets, methods and frameworks used in software defect prediction research from 2014 to 2020.Books on Demand GmbH, Überseering 33, 22297 Hamburg 140 pp. Englisch. Bestandsnummer des Verkäufers 9786203202496
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A COMPREHENSIVE APPROACH TOWARDS DEVELOPING INTELLIGENT SYSTEM
Verlag:
LAP LAMBERT Academic Publishing Feb 2021, 2021
ISBN 10: 6203202495
ISBN 13: 9786203202496
Neu
Taschenbuch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Designing Intelligent Software System for software defect prediction (SDP) is an important challenge in the field of software engineering using machine learning algorithms as class-imbalance problems cause difficulties for classification of defective and non-defective modules so Imbalanced learning deals with this problem and also used by researchers, but unfortunately with inconsistent results. For this, we conducted a comprehensive experiment for designing intelligent software system using the effect of imbalanced learning on imbalance dataset metrics, type of classifier, input metrics and imbalanced learning method. The major requirement in designing Intelligent Software System for software defect prediction typically uses methods and frameworks which allow software engineers to focus on development activities in terms of defect-prone code, thereby improving software quality and making better use of resources. Many software defect prediction datasets, methods and frameworks are complex, thus a comprehensive picture of defect prediction research from development phase is missing. This research aims to identify and analyse the research trends, datasets, methods and frameworks used in software defect prediction research from 2014 to 2020. 140 pp. Englisch. Bestandsnummer des Verkäufers 9786203202496
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A COMPREHENSIVE APPROACH TOWARDS DEVELOPING INTELLIGENT SYSTEM : INFORMATION SYSTEM DEVELOPMENT USING DATA ANALYSIS
Verlag:
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203202495
ISBN 13: 9786203202496
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Designing Intelligent Software System for software defect prediction (SDP) is an important challenge in the field of software engineering using machine learning algorithms as class-imbalance problems cause difficulties for classification of defective and non-defective modules so Imbalanced learning deals with this problem and also used by researchers, but unfortunately with inconsistent results. For this, we conducted a comprehensive experiment for designing intelligent software system using the effect of imbalanced learning on imbalance dataset metrics, type of classifier, input metrics and imbalanced learning method. The major requirement in designing Intelligent Software System for software defect prediction typically uses methods and frameworks which allow software engineers to focus on development activities in terms of defect-prone code, thereby improving software quality and making better use of resources. Many software defect prediction datasets, methods and frameworks are complex, thus a comprehensive picture of defect prediction research from development phase is missing. This research aims to identify and analyse the research trends, datasets, methods and frameworks used in software defect prediction research from 2014 to 2020. Bestandsnummer des Verkäufers 9786203202496
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