A Price Prediction Method Based on CatBoost

Tie Wang, Yutian Wang, Mingzhe Liu
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引用次数: 1

Abstract

We have studied a price prediction method based on CatBoost, which can evaluate and predict the value of objects. In our approach, we applied many advanced and popular techniques of feature engineering. Also, we compared and analyzed different models, including linear models, tree-based models, and deep learning in the modelling part. Specifically, we have applied it to the housing price prediction, which has verified the effectiveness of our method. Our method can not only be used to predict housing prices, but also to evaluate or predict the value of other objects, such as cultural objects or artworks.
基于CatBoost的价格预测方法
我们研究了一种基于CatBoost的价格预测方法,它可以评估和预测对象的价值。在我们的方法中,我们应用了许多先进和流行的特征工程技术。在建模部分,我们对不同的模型进行了比较和分析,包括线性模型、基于树的模型和深度学习模型。具体而言,我们将其应用于房价预测,验证了该方法的有效性。我们的方法不仅可以用来预测房价,也可以用来评估或预测其他物品的价值,比如文物或艺术品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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