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研究生:張維婷
研究生(外文):Wei-ting Chang
論文名稱:切割式空值估計在人力資源資料庫之研究
論文名稱(外文):Partitional approach for estimating null value in human resource database.
指導教授:鄭景俗鄭景俗引用關係
學位類別:碩士
校院名稱:國立雲林科技大學
系所名稱:資訊管理系碩士班
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:英文
論文頁數:57
中文關鍵詞:空值人力資源資料庫影響程度迴歸係數相關係數
外文關鍵詞:degree of influentialregression coefficientcorrelation coefficientnull valuehuman resource database
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在資訊化為導向的現代社會中,企業對資料庫的依賴愈來愈深,當資料庫中的某些屬性其屬性值為空值時,將會造成整個資料庫不能正常的運作,此時企業將遭受重大的損失。在本研究中,我們提出一個切割式的機制在人力資源資料庫具有空值時能有效地且更準確地估計空值。我們先採用逐步迴歸來選出資料庫中最重要的兩個屬性,且利用這兩個屬性來建立資料類別。建立好類別之後,針對每一類別中的資料進行分群。接著,計算每一群裡屬性之間的影響程度。本研究中有兩種計算影響程度的方式,一種是使用判定係數(陳鍚明 與 蕭信仁,2004),而另一種則是本研究採用的迴歸係數。利用此兩種方式進而來估計出資料庫之空值。最後,為了驗證我們提出之方法,採用一個實際的資料庫並利用平均絕對誤差率(MAER)來做為評估準則且做為比較之依據。
In general, a database system will not operate properly if it exist some null values of attributes in the system. In this study, we propose a partitional approach for estimating null values in human resource database, which utilize stepwise regression to select the first two important attributes from the database, then partition data by these two important attributes. After building up the data category, we apply the clustering method to cluster data. And next, calculate the degree of influential between the attributes. In this study, there are two ways to calculate the degree of influential. One is using coefficient of determination (Chen & Hsiao, 2004) and the other is using regression coefficients that presented in our study. Furthermore, estimate null values in the human resource database. For verifying our method, this study utilize mean of absolute error rate (MAER) as evaluation criterion to compare with Chen and Hsiao’s method.
1. Introduction 1
1.1 Background and Motivation 1
1.2 Research Objectives 3
1.3 Research Limitations 3
1.4 Organization of the Study 4
2. Literature Review 6
2.1 Review for Estimating Null Value 6
2.2 Stepwise Regression 7
2.3 Correlation Metric 8
2.3.1 Correlation coefficient and coefficient of determination 9
2.3.2 Regression coefficient 10
2.4 Clustering Method 12
2.5 Human Resource Database 14
3. Partitional Approach for Estimating Null Value 17
3.1 Research Framework 17
3.2 Partition Data by Important Attributes 19
3.3 Algorithm Process of Estimating Null Value 21
4. Verification and Comparison 29
5. System Development and Implement 35
5.1 Introduction of the System 35
5.2 The Result of the Experiment 38
6. Conclusions 45
References 47
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