This seminal work by Jiawei Han and Micheline Kamber offers a comprehensive exploration of data mining principles and practices. The authors delve into the intricacies of extracting meaningful patterns and insights from large datasets, providing readers with a robust understanding of this rapidly evolving field.
Data Mining: Concepts and Techniques by Jiawei Han and Micheline Kamber
相关推荐
Data Mining Concepts and Techniques (3rd Edition) Review
This review covers the third edition of Data Mining Concepts and Techniques. Written in accessible English, the epub format provides a pleasant reading experience in Adobe Digital Editions.
数据挖掘
3
2024-05-29
Transaction Processing Concepts and Techniques 中文版
《Transaction Processing Concepts and Techniques》是数据库领域的经典著作，详细阐述了数据库事务处理的理论和实践。书中介绍了事务的ACID特性：原子性确保所有操作要么全部完成要么全部不完成，一致性保证事务结束后数据库状态符合业务规则，隔离性防止并发事务干扰，持久性保证事务提交后结果永久保存。此外，还讨论了事务的提交、回滚和并发控制机制，以及分布式事务处理的挑战和解决方案。适合高校学生和数据库专业人士阅读。
MySQL
0
2024-08-12
Philosophical Insights in Data Mining
This English paper delves into the philosophical underpinnings of data mining, exploring its implications beyond technical methodologies. It employs specialized language to navigate complex concepts and theories, inviting readers to engage with the deeper significance of extracting knowledge from data.
数据挖掘
2
2024-05-16
Introduction to Massive Data Set Mining
Course PDF on mining of massive datasets, Chapter 1, introduces the concept of big data and its applications in various fields.
算法与数据结构
6
2024-07-13
Internet-Web-Technologies-BioMedical-Data-Mining IWT数据挖掘项目
这个名为\"IWT数据挖掘项目\"的项目由NIT RAIPUR的拉胡尔·何塞（Rahul Jose）主持，专注于将互联网网络技术应用于生物医学数据挖掘。项目利用先进的网络技术和数据分析工具从大量生物医学数据中提取有价值信息，推动医疗健康领域的科研和实践。互联网网络技术涵盖一系列用于创建、维护和使用互联网的协议、标准和技术，如HTTP、FTP、TCP/IP以及HTML、CSS和JavaScript等网页开发语言。在生物医学数据挖掘中，项目涉及数据收集、数据预处理、数据分析、可视化、数据安全与隐私、Web应用程序开发、云计算与大数据处理、实时与流式数据处理以及AI与深度学习等关键技术领域。
数据挖掘
3
2024-07-23
数据挖掘概念与技术（第二版）英文原著 Jiawei Han 机械工业出版社下载
各位朋友请放心下载《数据挖掘概念与技术（第二版）英文原著 Jiawei Han 机械工业出版社》的答案！
数据挖掘
2
2024-07-16
数据挖掘教程深入学习Data Mining A Tutorial-Based Primer
这本书是基于《Data Mining A Tutorial-Based Primer》翻译而来，全面介绍数据挖掘的基础知识和技术应用。书中详细解释了数据挖掘的流程及多种流行技术，特别展示了基于Excel的iDA数据挖掘工具。内容包括数据挖掘模型的建立与测试，结果的解释与验证，以及如何将数据挖掘技术应用于实际工作中。
数据挖掘
0
2024-08-24
Sophia Mining: 数据洞察利器
Sophia Mining 致力于通过数据挖掘和分析算法， 挖掘数据价值， 助您探索数据背后的故事。
数据挖掘
4
2024-04-29
Efficient Algorithms for Frequent Sequence Mining and Load Value Prediction
This research focuses on developing novel algorithms for two key areas: frequent sequence mining in transactional databases and enhanced load value prediction. A novel algorithm, SPAM (Sequential Pattern Mining Algorithm), is introduced to efficiently discover frequent sequences, even those of considerable length. SPAM leverages advanced pruning and indexing techniques to optimize its search. Furthermore, the research explores load value prediction (LVP) through identifying frequent patterns within program memory access traces. These discovered patterns serve as the foundation for developing efficient pre-fetching strategies, leading to improved performance.
Access
2
2024-07-01