本研究利用支持向量機(Support Vector Machine, SVM)來預測美髮從業人員的年度業績。運用已知的背景資料,包括教育程度、工作經驗及年資、年齡、性別以及美髮從業人員其若干屬性特質,利用SVM就可以將美髮從業人員的業績預測出來。為了確認本研究利用SVM所創建出來的預測模型是有效的並準確的,本研究收集某台灣知名美髮業者美髮從業人員真實的背景資料、履歷以及業績資料進行預測的驗證。本研究共蒐集51位美髮從業人員一年(民國103年至民國104年)的資料,並運用SVM進行預測。研究結果顯示支持向量機可以準確地預測出美髮從業人員的業績。除此之外,還可以做業績高低的分類,而本研究的分類結果也擁有高度的準確性。
In this paper we employ Support Vector Machines (SVM) to predict the annual turnover of hairdressers. Given the education level, experience year, age, gender, and some other attributes of a hairdresser, the annual turnover of the hairdresser can be predicted. To validate the prediction model, real data collected from a famous hair design company in Taiwan are used. These data included the profile of 51 hairdressers and their turnovers during 2014 to 2015. Results from this paper show that SVM can predict the turnover of a hairdresser accurately. In addition, the classification is done and its result shows a high accurate rate.