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200 1 $aPremodern financial system. A historical co mparative study
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200 00$aMachine learning applications in software engineering$b[electronic resource] /$feditors, Du Zhang, Jeffrey J.P. Tsai
210   $aHackensack,  N.J. ;$aHong Kong $cWorld Scientific$dc2005
215   $a1 online resource (367 p.)
225 1 $aSeries on software engineering and knowledge engineering ;$vv. 16
300   $aDescription based upon print version of record.
311   $a981-256-094-7 
320   $aIncludes bibliographical references (p. 345-355) and index.
327   $aACKNOWLEDGMENT; TABLE OF CONTENTS; Chapter 1 Introduction to Machine Learning and Software Engineering; Chapter 2 ML Applications in Prediction and Estimation; Chapter 3 ML Applications in Property and Model Discovery; Chapter 4 ML Applications in Transformation; Chapter 5 ML Applications in Generation and Synthesis; Chapter 6 ML Applications in Reuse; Chapter 7 ML Applications in Requirement Acquisition; Chapter 8 ML Applications in Management of Development Knowledge; Chapter 9 Guidelines and Conclusion; References
330   $aMachine learning deals with the issue of how to build computerprograms that improve their performance at some tasks throughexperience. Machine learning algorithms have proven to be of greatpractical value in a variety of application domains. Not surprisingly,the field of software engineering turns out to be a fertile groundwhere many software development and maintenance tasks could beformulated as learning problems and approached in terms of learningalgorithms.
410  0$aSeries on software engineering and knowledge engineering ;$vv. 16.
606   $aSoftware engineering
606   $aComputer software$xQuality control
606   $aComputer software$xEvaluation
606   $aMachine learning
615  0$aSoftware engineering.
615  0$aComputer software$xQuality control.
615  0$aComputer software$xEvaluation.
615  0$aMachine learning.
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