在金融市場、信息網(wǎng)絡(luò)以及電子商務(wù)等領(lǐng)域中積累了大量時間序列數(shù)據(jù)，對這些數(shù)據(jù)進行深層次的分析，是數(shù)據(jù)挖掘研究中的重要方向之一。Microsoft 時序算法是一個新的預(yù)測算法，使用Microsoft 時序算法創(chuàng)建的模型是一個自動回歸模型。本文用Microsoft 時序算法建立預(yù)測模型，預(yù)測某食品零售超市未來的銷售情況。
關(guān)鍵詞 時序算法；銷售預(yù)測；數(shù)據(jù)挖掘
Abstract: In fields as the financial market, the information network and electronic commerce lots of time series data are accumulated. The in-depth analysis of these data is one of the important directions of data mining. Microsoft timing series algorithm is new. The model based on Microsoft timing series algorithm is an automatic regression model. In this paper, a prediction model is set up through Microsoft timing series algorithms to forecast sales of food retail supermarket in future.
Key words: Time series algorithm; sales prediction; data mining(DM)