Application of Machine Learning in Business Forecasting:Factor Analysis
碩士 === 國立中正大學 === 數學系應用數學研究所 === 107 === This paper applies the methods of machine learning in business data from e-commerce, travel service, or insurance companies.Although these companies belong to different industries, they have the same purpose of reducing internal operating costs via shopping...
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ndltd-TW-107CCU005070102019-11-02T05:27:14Z http://ndltd.ncl.edu.tw/handle/nzjhg4 Application of Machine Learning in Business Forecasting:Factor Analysis 機器學習於商業資料預測上的應用:因素分析 LIN,CHIA-HSIN 林佳昕 碩士 國立中正大學 數學系應用數學研究所 107 This paper applies the methods of machine learning in business data from e-commerce, travel service, or insurance companies.Although these companies belong to different industries, they have the same purpose of reducing internal operating costs via shopping data analysis and consumer behavior forecasting. Recently, the speed and quantity of data collection is certainly far faster and larger than the past. Therefore, not only the traditional statistical Regression Analysis, Logistic regression, and Principal Component Analysis, but the machine learning methods developed in recent years, such as Neural Network, Support Vector Machine, Random Forest, XGboost are used in this paper. Through the comparing and discussing between these methods, we build up the forecasting models, search the key factors in the models, and interpret the observed phenomena. WANG, CHI-JEN 王琪仁 2019 學位論文 ; thesis 93 zh-TW |
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碩士 === 國立中正大學 === 數學系應用數學研究所 === 107 === This paper applies the methods of machine learning in business data from e-commerce, travel service, or insurance companies.Although these companies belong to different industries, they have the same purpose of reducing internal operating costs via shopping data analysis and consumer behavior forecasting. Recently, the speed and quantity of data collection is certainly far faster and larger than the past. Therefore, not only the traditional statistical Regression Analysis, Logistic regression, and Principal Component Analysis, but the machine learning methods developed in recent years, such as Neural Network, Support Vector Machine, Random Forest, XGboost are used in this paper. Through the comparing and discussing between these methods, we build up the forecasting models, search the key factors in the models, and interpret the observed phenomena.
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WANG, CHI-JEN |
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WANG, CHI-JEN LIN,CHIA-HSIN 林佳昕 |
author |
LIN,CHIA-HSIN 林佳昕 |
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LIN,CHIA-HSIN 林佳昕 Application of Machine Learning in Business Forecasting:Factor Analysis |
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LIN,CHIA-HSIN |
title |
Application of Machine Learning in Business Forecasting:Factor Analysis |
title_short |
Application of Machine Learning in Business Forecasting:Factor Analysis |
title_full |
Application of Machine Learning in Business Forecasting:Factor Analysis |
title_fullStr |
Application of Machine Learning in Business Forecasting:Factor Analysis |
title_full_unstemmed |
Application of Machine Learning in Business Forecasting:Factor Analysis |
title_sort |
application of machine learning in business forecasting:factor analysis |
publishDate |
2019 |
url |
http://ndltd.ncl.edu.tw/handle/nzjhg4 |
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