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Automatic Requirement Classification: A Comparative Study
Abstract
Software requirements must be classified for later use of requirements in the design and implementation phases. This classification can be done manually, which takes a lot of time and effort, or recently it can be done automatically. Automatic requirement classification is an important and promising area in both industry and research. Automatic classification of requirements is implemented using one of machine learning techniques. In this paper, a comparative study is introduced using one of machine learning techniques (Naïve Bayes) in order to observe the accuracy difference between two machine learning tools (Weka and RapidMiner) using a dataset of requirements.
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References
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