Xindong Wu, Vipin Kumar The Top Ten Algorithms in Data Mining. Chapman&Hall/CRC. 2009. 208Identifying some of the most influential algorithms that are widely used in the data mining community, The Top Ten Algorithms in Data Mining provides a description of each algorithm, discusses its impact, and reviews current and future research. Thoroughly evaluated by independent reviewers, each chapter focuses on a particular algorithm and is written by either the original authors of the algorithm or world-class researchers who have extensively studied the respective algorithm.The book concentrates on the following important algorithms: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. Examples illustrate how each algorithm works and highlight its overall performance in a real-world application. The text covers key topics—including classification, clustering, statistical learning, association analysis, and link mining—in data mining research and development as well as in data mining, machine learning, and artificial intelligence courses.By naming the leading algorithms in this field, this book encourages the use of data mining techniques in a broader realm of real-world applications. It should inspire more data mining researchers to further explore the impact and novel research issues of these algorithms.

吴新东，Vipin Kumar 《数据挖掘中的十大算法》。Chapman&Hall/CRC. 2009. 208确定了一些在数据挖掘界广泛使用的最有影响力的算法，《数据挖掘十大算法》对每一种算法进行了描述，讨论了其影响，并回顾了当前和未来的研究。经过独立评审员的彻底评估，每一章都专注于一种特定的算法，并由算法的原作者或广泛研究过相关算法的世界级研究人员撰写。本书集中介绍了以下重要算法。C4.5、k-Means、SVM、Apriori、EM、PageRank、AdaBoost、kNN、Naive Bayes和CART。实例说明了每种算法的工作原理，并强调了其在实际应用中的整体性能。本书涵盖了数据挖掘研究和开发以及数据挖掘、机器学习和人工智能课程中的关键主题--包括分类、聚类、统计学习、关联分析和链接挖掘。通过命名该领域的领先算法，本书鼓励在更广泛的现实世界应用中使用数据挖掘技术。它应该激励更多的数据挖掘研究人员进一步探索这些算法的影响和新的研究问题。