The contribution of this paper is comparing three popular machine learning methods for software fault prediction. They are classification tree, neural network and case-based reasoning. First, three different classifiers are built based on these three different approaches. Second, the three different classifiers utilize the same product metrics as predictor variables to identify the fault-prone components. Third, the predicting results are compared on two aspects, how good prediction capabilities these models are, and how the models support understanding a process represented by the data.
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机译:Arthrodesis and arthroplasty of the first metatarsophalangic joint in the treatment of Hallux Rigidus - comparative study of appropriately selected patients
机译:Arthrodesis and arthroplasty of the first metatarsophalangic joint in the treatment of Hallux Rigidus - comparative study of appropriately selected patients?