A Classical Fuzzy Approach for Software Effort Estimation on Machine Learning Technique

Details A Classical Fuzzy Approach for Software Effort Estimation on Machine Learning Technique A Classical Fuzzy Approach for Software Effort Estimation on Machine Learning Technique

2011-12-16

arxiv.org/abs/1112.3877v1

Computer Science

Software Engineering

5 pages, 2 figures, 4 tables

Scientific paper

Software Cost Estimation with resounding reliability,productivity and development effort is a challenging and onerous task. This has incited the software community to give much needed thrust and delve into extensive research in software effort estimation for evolving sophisticated methods. Estimation by analogy is one of the expedient techniques in software effort estimation field. However, the methodology utilized for the estimation of software effort by analogy is not able to handle the categorical data in an explicit and precise manner. A new approach has been developed in this paper to estimate software effort for projects represented by categorical or numerical data using reasoning by analogy and fuzzy approach. The existing historical data sets, analyzed with fuzzy logic, produce accurate results in comparison to the data set analyzed with the earlier methodologies.

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