波士顿房价预测:机器学习

Songyi Bai
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引用次数: 1

摘要

波士顿的住房问题已经被许多数据科学家研究了50多年。这个问题被证明是非常有利可图的,它被认为是最经典的机器学习问题之一。利用机器学习技术,计算机科学家已经将他们的估计误差降低到4%左右。为了解决这个问题,计算机科学家近年来开发了许多机器学习算法。有些很简单,有些则更复杂;有些提供了房屋价值的粗略估计,而另一些则提供了更精确的估计。在本文中,我们将看到他们如何使用机器学习回归方法来解决问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Boston house price prediction: machine learning
The Boston housing problem has been studied by many data scientists for over 50 years. The problem is proven to be extremely profitable, and it is considered as one of the most classical machine learning problems. Using machine learning techniques, computer scientists have already reduced the error of their estimation to around 4%. To solve this problem, computer scientists have developed a number of machine learning algorithms in recent years. Some are simple, while others are more complex; some offer a rough estimate of house value, while others offer more precise estimates In this essay we will see how they approach the problem using machine learning regression methods.
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