Application of Nonlinear Trees for Software Quality Assessment

• Main Authors: Nian-Cing Jhang, 張年慶
• Other Authors: 邱南星
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/46677865376099031597

碩士 === 清雲科技大學 === 資訊管理所 === 98 === Software quality in the software industry has gradually taken seriously. Therefore, many techniques From the data mining methods and artificial intelligence use to establish software quality classification models have been proposed. But finding a suitable method of establishing Prediction model is still a difficult task. The study is published in CTPSO to build software quality prediction model. This method uses the PSO to search for Non-linear function of Parameter. Using this approach produce Classification rules and Nodes. Further development of the Classification model to improve Decision Tree is hidden problem. This study used experimental data sets for the KC2. This method for comparison to C5.0, CART, CHAID, QUEST, ANN, LR, SVM and GP. The results showed that KC2 used CTPSO to produce better prediction results.