A Study on Prediction Model of the Automobile Maintenance Items using Data Mining Approach
碩士 === 崑山科技大學 === 資訊管理研究所 === 105 === Data analysis for vehicle maintenance analytics is crucial to explore the increasing trend of vehicle maintenance market which examines the significant factors of vehicle failure items from vehicle maintenance information. Accordingly, this study developed a dec...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2017
|
| Online Access: | http://ndltd.ncl.edu.tw/handle/bqc42h |
| Summary: | 碩士 === 崑山科技大學 === 資訊管理研究所 === 105 === Data analysis for vehicle maintenance analytics is crucial to explore the increasing trend of vehicle maintenance market which examines the significant factors of vehicle failure items from vehicle maintenance information. Accordingly, this study developed a decision tree analysis model by including the maintenance part, brand, and mileage and car age as leaf nodes to identify the revlevance of vehicle damaged parts. A cross-validation scheme was used for performing the regression analysis to examine failure problem with the relevant vehicle components using the data mining tool weka with R package. Finally, we discuss the association rules among vehicle failure items to provide a reference for future vehicle maintenance and spare parts for the stock preparation.
|
|---|