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Machine Learning Classification to Effort Estimation for Embedded Software Development Projects.

, , , and . Int. J. Softw. Innov., 5 (4): 19-32 (2017)

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Analysis of Source Codes by Beginners in Programming Education., , and . SNPD (2), page 774-781. IEEE Computer Society, (2007)Error Estimation Models Integrating Previous Models and Using Artificial Neural Networks for Embedded Software Development Projects., , , and . ICTAI (2), page 371-378. IEEE Computer Society, (2008)978-0-7695-3440-4.Classification on nonlinear mapping of reducts based on nearest neighbor relation., , , , and . ICIS, page 491-496. IEEE Computer Society, (2015)Incremental Reducts Based on Nearest Neighbor Relations and Linear Classifications., , , , , and . IIAI-AAI, page 528-533. IEEE, (2019)Using an Artificial Neural Network for Predicting Embedded Software Development Effort., , , and . SNPD, page 275-280. IEEE Computer Society, (2009)Quantitative Comparison of LOC of Beginners' Program Making Ability., , and . SNPD, page 53-58. IEEE Computer Society, (2009)Analysis of Mouth Shape Deformation Rate for Generation of Japanese Utterance Images Automatically., and . Software Engineering Research, Management and Applications, volume 578 of Studies in Computational Intelligence, page 75-86. Springer, (2014)A Proposal of Mouth Shapes Sequence Code for Japanese Pronunciation., , and . SNPD (Selected Papers), volume 368 of Studies in Computational Intelligence, page 55-65. Springer, (2011)Effort Estimation for Embedded Software Development Projects by Combining Machine Learning with Classification., , , and . ACIT/CSII/BCD, page 265-270. IEEE, (2017)Analyzing relationship between the number of errors in review processes for embedded software development projects., , , and . ICIS, page 485-490. IEEE Computer Society, (2015)