基于LSTM机器学习模型的逻辑回归准确预测比特币价格

H. Andi
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引用次数: 41

摘要

近年来,对机器学习和人工智能辅助交易的需求有所增加。为了从比特币市场中提取异常利润,使用了机器学习和人工智能(AI)辅助的交易过程。每天,数据都会保存指定的时间。这些方法与先进的算法相结合会产生很好的结果。算法和架构结构的结果推动了加密货币市场的发展。市值的空前增长使加密货币在2017年蓬勃发展。目前,市场共容纳1500种加密货币,所有加密货币都在活跃交易。挖掘加密货币并使用它来支付在线购物总是可能的。拟议的研究更侧重于通过对特定数据集的规范化来利用比特币价格的准确预测。通过使用LSTM机器学习,该数据集已经过训练,可以对比特币价格进行更准确的预测。此外,本研究工作评估了不同的机器学习方法,发现建议的工作提供了更好的结果。根据所得结果,计算了测试的准确度、召回率、精密度和灵敏度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
In recent years, there has been an increase in demand for machine learning and AI-assisted trading. To extract abnormal profits from the bitcoin market, the machine learning and artificial intelligence (AI) assisted trading process has been used. Each day, the data gets saved for the specified amount of time. These approaches produce great results when integrated with cutting-edge algorithms. The results of algorithms and architectural structures drive the development of cryptocurrency market. The unprecedented increase in market capitalization has enabled the cryptocurrency to flourish in 2017. Currently, the market accommodates totally 1500 cryptocurrencies, all of which are actively trading. It is always possible to mine the cryptocurrency and use it to pay for online purchases. The proposed research study is more focused on leveraging the accurate forecast of bitcoin prices via the normalization of a particular dataset. With the use of LSTM machine learning, this dataset has been trained to deploy a more accurate forecast of the bitcoin price. Furthermore, this research work has evaluated different machine learning methods and found that the suggested work delivers better results. Based on the resultant findings, the accuracy, recall, precision, and sensitivity of the test has been calculated.
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