Price prediction is one of the examples related to forecasting tasks and is a project based on data science. Price prediction analyzes data and predicts the cost of new products. The goal of this research is to achieve an arrangement to predict the price of a cellphone based on its specifications. So, five deep learning models are proposed to predict the price range of a cellphone, one unimodal and four multimodal approaches. The multimodal methods predict the prices based on the graphical and non-graphical features of cellphones that have an important effect on their valorizations. Also, to evaluate the efficiency of the proposed methods, a cellphone dataset has been gathered from GSMArena. The experimental results show 88.3% F1-score, which confirms that multimodal learning leads to more accurate predictions than state-of-the-art techniques.
翻译:价格预测是与预测任务有关的例子之一,是一个基于数据科学的项目。价格预测分析数据并预测新产品的成本。这项研究的目的是根据一个手机的规格做出预测价格的安排。因此,提出了五个深层次学习模型,以预测一个手机的价格范围、一种单一方式和四种多式联运方法。多式联运方法根据对手机的保值有重要影响的手机的图形和非图形特征预测价格。此外,为了评估拟议方法的效率,从GSMArena收集了一个手机数据集。实验结果显示88.3%的F1核心,这证实多式联运学习导致比最新技术更准确的预测。