论文标题
基于机器学习的启发式启发式，以预测在线销售的功效
A machine learning based heuristic to predict the efficacy of online sale
论文作者
论文摘要
仅仅从商品提供的折扣中，很难决定在线销售的功效。在确定折扣的重要性时，必须考虑的产品价格不同。在本文中，我们提出了一种基于机器学习的启发式，以量化任何商品提供的折扣的\ textit {“意义”}。我们提出的技术可以根据功能和原始价格量化折扣的重要性，因此可以通过预测销售的功效来指导买家。我们使用支持向量机在Flipkart夏季销售数据集上应用了此技术，该机器可预测销售的功效，精度为91.11 \％。我们的结果表明，在Flipkart Summer Sale期间，很少有手机有很大的折扣。
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.
