House Price Forecasting Based on Hybrid Multi-regression Model

Shivdutt Vishwakarma, Swasti Singhal
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Abstract

It is important to manage the production by analyzing the demand in the market. The market faces uncertain demands, short life cycle and lack of historical sales data due to which, forecasting becomes challenging. Various approaches have been proposed over the past few decades concerning this issue. This paper forms a basis for understanding the prediction mechanism by presenting a comprehensive literature review along with various domains in which sales forecasting can be done. For any prediction process we can’t define a certain model that will just outperform every other model but we can try and find suitable model according to the data. We have defined various models and also a hybrid model to predict the selling price of house based on its features, thus feature engineering is also applied to extract a fruitful dataset.
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基于混合多元回归模型的房价预测
通过分析市场需求来管理生产是很重要的。由于市场需求不确定,生命周期短,缺乏历史销售数据,因此预测变得具有挑战性。在过去的几十年里,关于这个问题提出了各种各样的方法。本文通过全面的文献综述以及可以进行销售预测的各个领域,为理解预测机制奠定了基础。对于任何预测过程,我们都不能定义一个特定的模型,它将优于其他所有模型,但我们可以根据数据尝试找到合适的模型。我们定义了各种模型和混合模型,根据房屋的特征来预测房屋的销售价格,从而应用特征工程提取了一个富有成效的数据集。
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