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論文名稱 Title |
綜合法則歸納系統中變項交互作用之延伸研究 Attribute Interaction Effects in the Composite Rule Induction System: An Extended Study |
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系所名稱 Department |
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畢業學年期 Year, semester |
語文別 Language |
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學位類別 Degree |
頁數 Number of pages |
66 |
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研究生 Author |
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指導教授 Advisor |
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召集委員 Convenor |
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口試委員 Advisory Committee |
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口試日期 Date of Exam |
2009-07-26 |
繳交日期 Date of Submission |
2009-08-25 |
關鍵字 Keywords |
資料探勘、法則歸納、二階法則、交互作用 Rule Induction, Data Mining, Interaction Effects, Second-order rules |
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統計 Statistics |
本論文已被瀏覽 5915 次,被下載 2 次 The thesis/dissertation has been browsed 5915 times, has been downloaded 2 times. |
中文摘要 |
Liang (1992) 所提出的『綜合法則歸納系統』(Composite Rule Induction System), 利用統計學的Tabular Approach 與Statistical Elaboration 方式,分別分析Qualitative 與 Quantitative 兩種特徵值來產生較精確之分類法則。在楊佶憲 (2007) 的後續研究中進一 步將綜合法則歸納系統改良為能夠產生與處理二階法則,當屬性之間存在交互作用時, 該系統便能有效處理二階的交互效果。 本研究利用事先篩選的機制,提出新的交互作用法則的產生方式以改善過去綜合法 則歸納系統中處理交互作用的方法,利用變數之間獨立的程度判斷是否產生該交互作用 法則,以改善因為二階法則使得系統複雜度過於龐大的問題。並針對混合資料中沒有處 理的類別屬性資料與連續屬性資料間二階假說法則的部分進行處理,使系統中的二階假 說法則能夠更完整。 為了評估改良後演算法的績效,本研究也開發出改良後的雛型系統,並與先前的雛 型系統進行比較,結果顯示本研究改良後的綜合法則歸納系統,其準確度與過去的系統 相等但是知識模型的複雜度可以顯著降低。 |
Abstract |
The Composite Rule Induction System proposed by Liang (1992) that uses the tabular approach and statistical inference to process qualitative and quantitative attributes separately for generating better classification rules. Yang (2007) extended the method by incorporating the second-order rules. This Study further extends the previous method by including a mechanism for detecting the existence of interaction effects. The detection method checks the degree of independence between attributes to determine whether the second-order rules should be processed. In order to evaluate the performance of the proposed method, an enhanced prototype system was developed and both real and simulated data were used to compare its accuracy and rule complexity with existing systems. The result shows that the enhanced system performs at least as accurate as the existing system but is significantly better in the complexity of the resulting knowledge base. |
目次 Table of Contents |
第一章、 緒論 ............................................................................................................................................ 1 第一節. 研究背景與動機 ............................................................................................................... 1 第二節. 研究目的 ........................................................................................................................... 3 第三節. 研究步驟與方法 ............................................................................................................... 4 第四節. 論文架構 ........................................................................................................................... 6 第二章、 文獻探討 .................................................................................................................................... 7 第一節. 資料探勘 ........................................................................................................................... 7 第二節. 決策樹歸納學習法 ........................................................................................................... 9 第三節. 綜合法則歸納系統 ......................................................................................................... 12 第四節. 綜合法則歸納系統之交互作用處理 ............................................................................. 21 第五節. 屬性之間的交互作用 ..................................................................................................... 24 第三章、 演算法改良 ............................................................................................................................... 27 第一節. 評估屬性之間的交互作用 ............................................................................................. 27 第二節. 建立類別型資料與非類別型資料的交互作用法則 ..................................................... 32 第四章、 績效評估 .................................................................................................................................. 34 第一節. 實驗一:真實資料集測試 ............................................................................................. 34 第二節. 實驗二:模擬資料集測試一 ......................................................................................... 43 第三節. 實驗三:模擬資料集測試二 ......................................................................................... 47 第五章、 結論 .......................................................................................................................................... 50 第一節. 研究貢獻 ......................................................................................................................... 50 第二節. 研究限制 ......................................................................................................................... 50 第三節. 後續研究建議 ................................................................................................................. 51 參考文獻 ……………………………………………………………………………………………..52 中文部分.......................................................................................................................................... 52 英文部分.......................................................................................................................................... 52 附錄一:雛型系統操作說明 ..................................................................................................................... 56 附錄二:SPSS 相關性資料產生巨集程式碼 ........................................................................................... 61 |
參考文獻 References |
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