現今,人們的生活型態以及飲食習慣大幅改變,因而引起一些疾病,導致身體亮紅燈。也因為這些病因,人們開始注重身體的健康保健,來降低各種疾病發生的機率。本研究是以資料探勘分類技術中的決策樹理論,應用於乳癌之預測。經分析後可驗證哪些屬性變數會引起乳癌。本研究採用UCI資料庫之Breast Cancer Wisconsin (Original)總共有699筆樣本資料,刪除16筆遺漏值,共採用683筆資料。因此,本研究採用資料探勘Weka軟體中的方法,包含J48、NB Tree、Naïve Bayes、Bayes Net、Multi-Layer Perceptron等演算法,分別比較所檢測出來的準確度結果,並且利用混淆矩陣做分類分析的比較。另外,運用統計分析工具來檢測屬性變數重要程度之結果,來探討乳癌相關的病因。進一步地,使用由Java語言構成且執行效率良好的JFuzzyLogic模糊邏輯推論系統開發工具,運用規則決策分析相關之理論,針對乳癌來發展一套風險評估系統。藉由相關知識參考並使用C++語言撰寫規則方法,結合開發工具中所提供的推論機制應用,進而提供使用者一個決策及評估參考的依據。本研究結果可以輔助民眾做簡易的乳癌預測,並亦可提供給醫師做診斷時之分析參考。
People nowadays have changed a lot in terms of life style and dietary habits, which tend to cause health problems and make the body sick. Not until this happens are people really willing to start paying attention to health issues more, trying to reduce the chance of falling ill. In this study, we apply decision tree theory of data mining in the prediction of breast cancer. After the analysis, we can verify which sorts of qualitative variables may mean cancer potential. This research has collected 699 data from Breast Cancer Wisconsin (Original) UCI; however, the exact number in use, except for the 16 data missed, is 683. The algorithms of J48, NB tree, Naive Bayes, Bayes Net, and Multi-Layer Perceptron implemented in the Weka software are also adopted to compare respectively and help get the accuracy of the results. Confusion matrix is used in categorization analysis. In addition, statistical analysis is applied in judging the importance of qualitative variables and finding the cause of breast cancer. Moreover, this study uses JFuzzLogic package, which programmed using Java language, and some theories related to regular decision analysis to develop a risk assessment system solely for detecting breast cancer. Through the reference of related knowledge and the use of C++, the study combine the different inference mechanisms used in this study and make them a basis for the user in both decision making and assessing. The results showed in this thesis can help people to make their own breast-cancer checks primarily and also can be a useful reference for a doctor when he/she diagnoses whether a patient with breast cancer or not.