Using Data Mining Technique To Build Cash Prediction：An Application Of Decision Trees

• Main Authors: Wang, Peiwen, 王珮紋
• Other Authors: Wu, Hsuche
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/87823544665254884322

碩士 === 國立中正大學 === 會計與資訊科技研究所 === 100 === Cash is very important property for enterprises, but it pays less attention rather than all the assets in the enterprises.The enterprises choose to hold some cash in spite of assets have higher reward after investment. According to the statistics of previous study, especially high-tech electronics industry always has high cash holdings.The high-tech electronics industry spent huge expenses.That means the company may incur the situation of insufficient funds. It is necessary to prepare a certain amount of cash. This paper uses setpwise regression analysis to find suitable variables for cash holdings of high-tech electronics industry in Taiwan. The selected ratios include the cash dividend payout、rate of research costs、leverage、liability、operating cash flow、investment cash flow、financing cash flow、ratio of operating cash flow, ratio of cash flow, size of the company. Using decision tree methods (AD Tree、Decision stump、 J48、NB Tree、LMT、Random Forest、Random Tree、REP Tree、Simple CART) to predict the accurate rate after classification by decision tree methods.This study have three experiments, namely: (1) the predictive ability of the decision tree algorithm; (2) of the decision tree algorithm with performance improvement algorithm; (3) choose the best decision tree forecast rate comparison with the logistic regression model. In three experiments, the Random Forest is the highest and better rate than the prediction of the logistic regression model.