The Top Ten Algorithms in Data Mining (Hardcover)

The Best-Known Algorithms Currently Used in the Data Mining Community
Contributions from recognized leaders in the field

Identifying 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.

《資料探勘社群中目前最知名的演算法》是一本由該領域的知名領袖所貢獻的書籍。本書介紹了一些在資料探勘社群中廣泛使用且具有影響力的演算法，並討論了每個演算法的影響力以及目前和未來的研究。每一章節都由該演算法的原始作者或深入研究該演算法的世界級研究人員撰寫，並經過獨立評審的嚴格評估。

本書重點介紹了以下重要演算法：C4.5、k-Means、SVM、Apriori、EM、PageRank、AdaBoost、k-NN、Naive Bayes和CART。書中通過實例展示了每個演算法的工作原理，並突出了它們在實際應用中的整體性能。本書涵蓋了資料探勘研究和開發中的關鍵主題，包括分類、聚類、統計學習、關聯分析和鏈結探勘，同時也適用於資料探勘、機器學習和人工智慧課程。

通過列舉這個領域中的領先演算法，本書鼓勵在更廣泛的實際應用領域中使用資料探勘技術。它應該能激發更多資料探勘研究人員進一步探索這些演算法的影響和新穎研究議題。