Chapman & Hall/CRC Data Mining and Knowledge Discovery Series
About the Book Series
As the field of data mining and knowledge discovery continues to grow, the timely dissemination of emerging research has become increasingly important both in math and stats, as well as across a range of disciplines seeking to take advantage of the wealth of data made available through informatics. This series aims to capture new developments and applications in data mining and knowledge discovery, while summarizing the computational tools and techniques useful in data analysis. This series is being established to encourage the integration of mathematical, statistical, and computational methods and techniques through the publication of a broad range of textbooks, reference works, and handbooks. We are looking to include those single author and contributed works that will—
- Provide introductory and advanced instructional and reference material for students and professionals in the mathematical, statistical, and computational sciences
- Supply researchers with the latest discoveries and the resources they need to advance the field
- Offer assistance to those interdisciplinary researchers and practitioners seeking to make use of data mining technology without advanced mathematical backgrounds
The inclusion of concrete examples and applications is highly encouraged. The scope of the series includes, but is not limited to, titles in the areas of data mining and knowledge discovery methods and applications, modeling, algorithms, theory and foundations, data and knowledge visualization, data mining systems and tools, and privacy and security issues. We are willing to consider other relevant topics that might be proposed by potential contributors.
Exploratory Data Analysis Using R
2nd Edition
By Ronald K. Pearson
May 22, 2026
Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA), and this revised edition is accompanied by the R package ExploreTheData that implements many of the approaches described. As before, the primary focus of the book is on identifying "...
Data Science and Machine Learning for Non-Programmers: Using SAS Enterprise Miner
1st Edition
By Dothang Truong
December 31, 2025
As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this ...
Demystifying AI: Data Science and Machine Learning Using IBM SPSS Modeler
1st Edition
By Dothang Truong
December 16, 2025
As artificial intelligence advances at an exponential pace, understanding data science and machine learning has become increasingly essential. Yet, the wide range of available resources can be daunting, posing challenges for beginners. This second book builds on the foundation laid in the first, ...
Data Science and Analytics with Python
2nd Edition
By Jesús Rogel-Salazar
June 02, 2025
Since the first edition of “Data Science and Analytics with Python” we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business ...
Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data
1st Edition
Edited
By Anuj Karpatne, Ramakrishnan Kannan, Vipin Kumar
August 26, 2024
Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of ...
Data Classification: Algorithms and Applications
1st Edition
Edited
By Charu C. Aggarwal
September 30, 2020
Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification...
Industrial Applications of Machine Learning
1st Edition
By Pedro Larrañaga, David Atienza, Javier Diaz-Rozo, Alberto Ogbechie, Carlos Esteban Puerto-Santana, Concha Bielza
September 30, 2020
Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces ...
Automated Data Analysis Using Excel
2nd Edition
By Brian D. Bissett
August 19, 2020
This new edition covers some of the key topics relating to the latest version of MS Office through Excel 2019, including the creation of custom ribbons by injecting XML code into Excel Workbooks and how to link Excel VBA macros to customize ribbon objects. It now also provides examples in using ...
Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation
1st Edition
By Scott Spangler
June 30, 2020
Unstructured Mining Approaches to Solve Complex Scientific ProblemsAs the volume of scientific data and literature increases exponentially, scientists need more powerful tools and methods to process and synthesize information and to formulate new hypotheses that are most likely to be both true and ...
Data Mining with R: Learning with Case Studies, Second Edition
2nd Edition
By Luis Torgo
June 30, 2020
Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material, ...
Event Mining: Algorithms and Applications
1st Edition
Edited
By Tao Li
June 30, 2020
Event mining encompasses techniques for automatically and efficiently extracting valuable knowledge from historical event/log data. The field, therefore, plays an important role in data-driven system management. Event Mining: Algorithms and Applications presents state-of-the-art event mining ...
Exploratory Data Analysis Using R
1st Edition
By Ronald K. Pearson
June 30, 2020
Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to ...