基于LightGBM集合方法的库存量预测

International journal of scientific and engineering research Pub Date : 2020-10-25 DOI:10.14299/ijser.2020.10.05

Vatsal Mitesh Tailor

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引用次数: 0

摘要

本文利用LightGBM集成方法来预测股票价格。首先，从日期中提取时间特征，并使用这些生成的特征构建回归模型。对特斯拉和可口可乐的股票历史数据进行了实验，以证明该方法在预测股价方面的有效性

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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Exploiting LightGBM Ensemble Method for Stock Prediction

This paper leverages the LightGBM Ensemble Method to predict stock prices. First, the time features are from the dates and these generated features are used to build a regression model. Experiments are performed on the Tesla and the Coca Cola stock historical data to show the effectiveness of the method in predicting stock prices

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International journal of scientific and engineering research

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