DocumentCode :
3636687
Title :
Analogies and Differences between Machine Learning and Expert Based Software Project Effort Estimation
Author :
Juan J. Cuadrado-Gallego;Pablo Rodríguez-Soria;Borja Martín-Herrera
Author_Institution :
Dept. de Cienc. de la Comput., Univ. de Alcala, Alcala de Henares, Spain
fYear :
2010
Firstpage :
269
Lastpage :
276
Abstract :
This paper presents a review and comparison of the software project cost estimation methods that have emerged with more impact in recent years; Expertise and Machine Learning methods. These methods and models have been selected according to an own criteria focusing onto Analogy estimation models and Case Based Reasoning approaches, assuming that they are widely utilized by researchers and with good accurate results. Finally we show a comparative analysis of the seven models proposed inside the Machine Learning methods with advantages and disadvantages between them.
Keywords :
"Machine learning","Costs","Machine learning algorithms","Distributed computing","Learning systems","Programming","Speech recognition","Software engineering","Artificial intelligence","Computer networks"
Publisher :
ieee
Conference_Titel :
Software Engineering Artificial Intelligence Networking and Parallel/Distributed Computing (SNPD), 2010 11th ACIS International Conference on
Print_ISBN :
978-1-4244-7422-6
Type :
conf
DOI :
10.1109/SNPD.2010.47
Filename :
5521533
Link To Document :
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