A Fuzzy Piecewise Regression Model with Change-point Detection
博士 === 國立交通大學 === 資訊管理所 === 87 === The possibilistic regression analysis proposed by Tanaka and Ishibuchi, which is extremely sensitive to outliers, may not able to find feasible solution. Besides, when they use linear programming in possibilistic regression analysis, some coefficients are limited t...
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ndltd-TW-087NCTU03960292016-07-11T04:13:35Z http://ndltd.ncl.edu.tw/handle/98190298945413986532 A Fuzzy Piecewise Regression Model with Change-point Detection 偵測改變點之模糊逐段迴歸模式 Yu Jing Rung 余菁蓉 博士 國立交通大學 資訊管理所 87 The possibilistic regression analysis proposed by Tanaka and Ishibuchi, which is extremely sensitive to outliers, may not able to find feasible solution. Besides, when they use linear programming in possibilistic regression analysis, some coefficients are limited to be crisp because of the characteristic of linear programming. To overcome large variation problem, we propose fuzzy piecewise regression method. Our method can also treat the problem with crisp coefficients by utilizing quadratic programming approach. The proposed fuzzy piecewise regression method has two advantages: (a) It can detect the positions of change-points and can estimate the fuzzy piecewise regression model simultaneously; (b) It can deal with outliers by automatically segmenting the data. Li Han Lin 黎漢林 1999 學位論文 ; thesis 61 en_US |
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博士 === 國立交通大學 === 資訊管理所 === 87 === The possibilistic regression analysis proposed by Tanaka and Ishibuchi, which is extremely sensitive to outliers, may not able to find feasible solution. Besides, when they use linear programming in possibilistic regression analysis, some coefficients are limited to be crisp because of the characteristic of linear programming. To overcome large variation problem, we propose fuzzy piecewise regression method. Our method can also treat the problem with crisp coefficients by utilizing quadratic programming approach. The proposed fuzzy piecewise regression method has two advantages: (a) It can detect the positions of change-points and can estimate the fuzzy piecewise regression model simultaneously; (b) It can deal with outliers by automatically segmenting the data.
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Li Han Lin |
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Li Han Lin Yu Jing Rung 余菁蓉 |
author |
Yu Jing Rung 余菁蓉 |
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Yu Jing Rung 余菁蓉 A Fuzzy Piecewise Regression Model with Change-point Detection |
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Yu Jing Rung |
title |
A Fuzzy Piecewise Regression Model with Change-point Detection |
title_short |
A Fuzzy Piecewise Regression Model with Change-point Detection |
title_full |
A Fuzzy Piecewise Regression Model with Change-point Detection |
title_fullStr |
A Fuzzy Piecewise Regression Model with Change-point Detection |
title_full_unstemmed |
A Fuzzy Piecewise Regression Model with Change-point Detection |
title_sort |
fuzzy piecewise regression model with change-point detection |
publishDate |
1999 |
url |
http://ndltd.ncl.edu.tw/handle/98190298945413986532 |
work_keys_str_mv |
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