一种基于机器学习的启发式在线销售效果预测方法
A machine learning based heuristic to predict the efficacy of online sale
摘要：
很难仅仅从商品的折扣来判断网上销售的有效性。不同的特征对产品的价格有不同的影响，在确定折扣的重要性时必须加以考虑。在本文中，我们提出了一个机器学习为基础的启发式量化的\textit{"significance"}的折扣提供任何商品。我们所提出的技术可以量化的基础上的功能和原始价格的折扣的意义，因此可以指导买家在销售季节通过预测销售的功效。我们已经使用支持向量机在Flipkart夏季销售数据集上应用了这种技术，该数据集预测销售的有效性，准确率为91.11%。我们的研究结果表明，很少有手机在Flipkart夏季销售期间有显着折扣。
英文摘要：
It is difficult to decide upon the efficacy of an online sale simply from the discount offered on commodities. Different features have different influence on the price of a product which must be taken into consideration when determining the significance of a discount. In this paper we have proposed a machine learning based heuristic to quantify the \textit{"significance"} of the discount offered on any commodity. Our proposed technique can quantify the significance of the discount based on features and the original price, and hence can guide a buyer during a sale season by predicting the efficacy of the sale. We have applied this technique on the Flipkart Summer Sale dataset using Support Vector Machine, which predicts the efficacy of the sale with an accuracy of 91.11\%. Our result shows that very few mobile phones have a significant discount during the Flipkart Summer Sale.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
