Utilizing Machine Learning to Predict the Number of Bikes in an Area

Pub Date : 2023-05-31 DOI:10.47611/jsrhs.v12i2.4220
Tavishi Bansal, G. Goldsztein
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Abstract

Machine learning is a type of Artificial Intelligence that uses data to make predictions and improve the accuracy of its outcomes. In this article, the problem discussed is classified as supervised learning and the technique utilized is Logistic Regression. After a description detailing what supervised learning and logistic regression are, using a data set to develop a model which predicts the number of bikes a rental bike company should provide based on certain conditions is discussed. The accuracy of this model is also communicated and the challenges and how the final estimations were reached are covered.
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利用机器学习来预测一个区域内自行车的数量
机器学习是一种人工智能,它使用数据进行预测并提高结果的准确性。在本文中,讨论的问题被归类为监督学习,使用的技术是逻辑回归。在详细描述了什么是监督学习和逻辑回归之后,讨论了使用数据集开发一个模型,该模型可以根据某些条件预测租赁自行车公司应该提供的自行车数量。该模型的准确性也进行了沟通,并涵盖了挑战以及如何达到最终估计。
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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