Precise estimation of software development exertion is basic in software designing. Thinks little of lead to time weights that may bargain full useful development and intensive testing of software. Interestingly, overestimates can bring about noncompetitive contract offers as well as over designation of development assets and work force. Thus, numerous models for assessing software development exertion have been proposed. This work portrays principles of machine learning, which we use to manufacture estimators of software development exertion from recorded information. Our work demonstrates that these strategies are focused with conventional estimators on one dataset, yet additionally delineate that these techniques are delicate to the information on which they are prepared. This preventative note applies to any model-development procedure that depends on authentic information. Every single such model for software exertion estimation ought to be assessed by investigating model affectability on an assortment of authentic information.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Precise estimation of software development exertion is basic in software designing. Thinks little of lead to time weights that may bargain full useful development and intensive testing of software. Interestingly, overestimates can bring about noncompetitive contract offers as well as over designation of development assets and work force. Thus, numerous models for assessing software development exertion have been proposed. This work portrays principles of machine learning, which we use to manufacture estimators of software development exertion from recorded information. Our work demonstrates that these strategies are focused with conventional estimators on one dataset, yet additionally delineate that these techniques are delicate to the information on which they are prepared. This preventative note applies to any model-development procedure that depends on authentic information. Every single such model for software exertion estimation ought to be assessed by investigating model affectability on an assortment of authentic information. 52 pp. Englisch. Codice articolo 9786138914723
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. Neuware -Precise estimation of software development exertion is basic in software designing. Thinks little of lead to time weights that may bargain full useful development and intensive testing of software. Interestingly, overestimates can bring about noncompetitive contract offers as well as over designation of development assets and work force. Thus, numerous models for assessing software development exertion have been proposed. This work portrays principles of machine learning, which we use to manufacture estimators of software development exertion from recorded information. Our work demonstrates that these strategies are focused with conventional estimators on one dataset, yet additionally delineate that these techniques are delicate to the information on which they are prepared. This preventative note applies to any model-development procedure that depends on authentic information. Every single such model for software exertion estimation ought to be assessed by investigating model affectability on an assortment of authentic information.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. Codice articolo 9786138914723
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Precise estimation of software development exertion is basic in software designing. Thinks little of lead to time weights that may bargain full useful development and intensive testing of software. Interestingly, overestimates can bring about noncompetitive contract offers as well as over designation of development assets and work force. Thus, numerous models for assessing software development exertion have been proposed. This work portrays principles of machine learning, which we use to manufacture estimators of software development exertion from recorded information. Our work demonstrates that these strategies are focused with conventional estimators on one dataset, yet additionally delineate that these techniques are delicate to the information on which they are prepared. This preventative note applies to any model-development procedure that depends on authentic information. Every single such model for software exertion estimation ought to be assessed by investigating model affectability on an assortment of authentic information. Codice articolo 9786138914723
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Exercising machine language paradigms in software engineering | A Quick Primer | Manas Kumar Yogi (u. a.) | Taschenbuch | 52 S. | Englisch | 2019 | Scholars' Press | EAN 9786138914723 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Codice articolo 117630706
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