Churn Prediction with CNN model in Nutrient Supplement Industry
碩士 === 國立中央大學 === 企業管理學系 === 107 === There is no nutrient supplement industry in the current study of customer churn or change, and there is no clear definition of total churn and partial churn. This thesis may be the first research of the customer churn of nutrient supplement industry, and a clear...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2019
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| Online Access: | http://ndltd.ncl.edu.tw/handle/9h58hs |
| Summary: | 碩士 === 國立中央大學 === 企業管理學系 === 107 === There is no nutrient supplement industry in the current study of customer churn or change,
and there is no clear definition of total churn and partial churn. This thesis may be the first
research of the customer churn of nutrient supplement industry, and a clear definition is given
for partial churn used in this thesis. Join another facet other than the most important facet of
loyalty about customer churn research—trust. Using Convolutional Neural Network(CNN) to
determine if the customer will churn. The results show that the Convolutional Neural Network
is indeed superior to the SVM.
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