OverviewMachine learning (ML) is rapidly being adopted by archaeologists interested in analyzing a range of geospatial, material cultural, textual, natural, and artistic data. The algorithms are particularly suited toward rapid identification and classification of archaeological features and objects. The results of these new studies include identification of many new sites around the world and improved classification of large archaeological datasets. ML fits well with more traditional methods used in archaeological analysis, and it remains subject to both the benefits and difficulties of those approaches. Small datasets associated with archaeological work make ML vulnerable to hidden complexity, systemic bias, and high validation costs if not managed appropriately. ML's scalability, flexibility, and rapid development, however, make it an essential part of twenty-first-century archaeological practice. This review briefly describes what ML is, how it is being used in archaeology today, and where it might be used in the future for archaeological purposes.

中文翻译：

---

机器学习进入考古领域

概述机器学习 (ML) 正在迅速被有兴趣分析一系列地理空间、物质文化、文本、自然和艺术数据的考古学家采用。该算法特别适用于考古特征和对象的快速识别和分类。这些新研究的结果包括识别世界各地的许多新遗址和改进大型考古数据集的分类。ML 非常适合考古分析中使用的更传统的方法，并且它仍然受到这些方法的好处和困难的影响。如果管理不当，与考古工作相关的小型数据集会使机器学习容易受到隐藏的复杂性、系统性偏差和高验证成本的影响。然而，ML 的可扩展性、灵活性和快速开发，使其成为二十一世纪考古实践的重要组成部分。这篇评论简要描述了机器学习是什么，它在今天的考古学中是如何使用的，以及它在未来可能用于考古目的的地方。