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Prediction of Sales Value in Online shopping using Linear Regression

机译:基于线性回归的在线购物销售价值预测

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The aim of this paper is to analyze the sales of a big superstore, and predict their future sales for helping them to increase their profits and make their brand even better and competitive as per the market trends by generating customer satisfaction as well. The technique used for prediction of sales is the Linear Regression Algorithm, which is a famous algorithm in the field of Machine Learning. The sales data is from the year 2011-13 and prediction of data for the year 2014 is done. Then, real-time data of the year 2014 is also taken and the actual data of the year 2014 has been compared to the predicted data to calculate the accuracy of prediction. This is done so as to validate our results with the actual ones. This in turn would help them take necessary actions (which has been discussed later) for their increase their sales.
机译:本文的目的是分析一家大型超市的销售情况,并预测其未来的销售情况,以帮助他们增加利润,并通过产生客户满意度来根据市场趋势使他们的品牌更好,更具竞争力。用于预测销售的技术是线性回归算法,它是机器学习领域中的著名算法。销售数据来自2011-13年,并完成了2014年的数据预测。然后,还获取2014年的实时数据,并将2014年的实际数据与预测数据进行比较,以计算预测的准确性。这样做是为了用实际结果验证我们的结果。反过来,这将有助于他们采取必要的措施(稍后将进行讨论)以增加销售额。

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