A Model for Missing Value Processing in Database with Self-Organizing Map
碩士 === 國立臺灣科技大學 === 電子工程系 === 90 === In this thesis, we propose a method that uses Self-Organizing Feature Map and Fuzzy Set Theory to process the data with missing value problem in database. In real world, the data we collected are not complete, and have the problem of missing value. If we analyze...
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ndltd-TW-090NTUST4280062015-10-13T14:41:23Z http://ndltd.ncl.edu.tw/handle/66744883922564150909 A Model for Missing Value Processing in Database with Self-Organizing Map 應用自組特徵映射網路於資料庫內遺失值之處理 Yu-Hsiang Chiu 邱鈺翔 碩士 國立臺灣科技大學 電子工程系 90 In this thesis, we propose a method that uses Self-Organizing Feature Map and Fuzzy Set Theory to process the data with missing value problem in database. In real world, the data we collected are not complete, and have the problem of missing value. If we analyze it directly, we usually can not get useful information, and the result of analysis will not be correct. The method we proposed is based on Self-Organizing Feature Map to analyze the data in database, and we use Fuzzy Set Theory to fuzzify the output neurons. Then we can compute values for the data with missing value. By this method, we hope to fulfill the needs of data preprocessing in Knowledge Discovery in Database, and improve the correctness of the follow-up analysis. We also implement this method and use the air quality monitoring data to justify the feasibility of the method we proposed. Chen-Chau Yang 楊鍵樵 2002 學位論文 ; thesis 59 zh-TW |
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碩士 === 國立臺灣科技大學 === 電子工程系 === 90 === In this thesis, we propose a method that uses Self-Organizing Feature Map and Fuzzy Set Theory to process the data with missing value problem in database. In real world, the data we collected are not complete, and have the problem of missing value. If we analyze it directly, we usually can not get useful information, and the result of analysis will not be correct. The method we proposed is based on Self-Organizing Feature Map to analyze the data in database, and we use Fuzzy Set Theory to fuzzify the output neurons. Then we can compute values for the data with missing value. By this method, we hope to fulfill the needs of data preprocessing in Knowledge Discovery in Database, and improve the correctness of the follow-up analysis. We also implement this method and use the air quality monitoring data to justify the feasibility of the method we proposed.
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Chen-Chau Yang |
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Chen-Chau Yang Yu-Hsiang Chiu 邱鈺翔 |
author |
Yu-Hsiang Chiu 邱鈺翔 |
spellingShingle |
Yu-Hsiang Chiu 邱鈺翔 A Model for Missing Value Processing in Database with Self-Organizing Map |
author_sort |
Yu-Hsiang Chiu |
title |
A Model for Missing Value Processing in Database with Self-Organizing Map |
title_short |
A Model for Missing Value Processing in Database with Self-Organizing Map |
title_full |
A Model for Missing Value Processing in Database with Self-Organizing Map |
title_fullStr |
A Model for Missing Value Processing in Database with Self-Organizing Map |
title_full_unstemmed |
A Model for Missing Value Processing in Database with Self-Organizing Map |
title_sort |
model for missing value processing in database with self-organizing map |
publishDate |
2002 |
url |
http://ndltd.ncl.edu.tw/handle/66744883922564150909 |
work_keys_str_mv |
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