Research on the Diamond Price Prediction based on Linear Regression, Decision Tree and Random Forest

Authors

  • Zhe OuYang

DOI:

https://doi.org/10.54097/13ccwv59

Keywords:

Multiple Linear Regression, Decision Tree Regression, Random Forest Regression, Diamond Price Prediction

Abstract

Diamonds are the symbol of the pure and indestructible love and the luxury that people have always sought after. However, because people know less about diamonds, they often only rely on the introduction of salespeople and jewelers in diamond trading. Therefore, it is difficult for consumers to buy diamonds of equal value and price. To solve this problem, this paper uses Multiple Linear Regression model, Decision Tree Regression model and Random Forest Regression model to predict diamond prices based on various diamond evaluation metrics in data set, so that consumers can intuitively learn about the normal price of the evaluation metrics of selected diamonds. Through this paper, it is found that the Random Forest Regression model has the best fitting and predictive ability in diamond prediction task, which is also the most recommended model.

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Published

22-01-2024

How to Cite

OuYang, Z. (2024). Research on the Diamond Price Prediction based on Linear Regression, Decision Tree and Random Forest. Highlights in Business, Economics and Management, 24, 248-257. https://doi.org/10.54097/13ccwv59