**2026 Textbook and Academic Authors Association (TAA) Textbook Excellence "Texty" Award Winner**Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated new edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going,...

Medical ethics draws upon methods from a wide array of disciplines, including anthropology, economics, epidemiology, health services research, history, law, medicine, nursing, philosophy, psychology, sociology, and theology.In this influential book, outstanding scholars in medical ethics bring these many methods together in one place to be systematically described, critiqued, and challenged. Newly revised and updated chapters in this second edition include philosophy, religion and ...

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the...

The tradition of tax-exempt status for nonprofit "charitable" organizations is well established, and few would argue with the principle. But the tax-exempt sector of the economy is vast and rapidly growing, resulting in the loss of billions of dollars of tax revenue. At the same time, we have no consensus on what purpose the charitable tax exemption serves, let alone agreement on what constitutes a charity. In this important addition to the theory of tax law, Colombo and Hall develop an or...

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods ...

THE BOOK THAT BREAKS A CRYPTOZOOLOGICAL TABOO!Do giant primates larger than gorillas, taller than Sasquatch and Yetis, still exist in the remotest corners of the globe? Famed cryptozoologists Mark A. Hall and Loren Coleman join forces to share their knowledge of this unexplored and neglected topic in cryptozoology.Bigfoot researchers have long been mystified, even embarrassed, by reports of giant hairy apes larger than Bigfoot, and as a result eyewitness re...

How to care for, store, display and interpret human remains, and issues of their ownership, are contentious questions, ones that need to be answered with care and due consideration. This book offers a systematic overview of the responses made by museums and other repositories in the United Kingdom, providing a baseline for understanding the scope and nature of human remains collections and the practices related to their care. The introduction sets UnitedKingdom practices within an internat...

Data Mining, Second Edition, describes data mining techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights of this new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; compreh...

Data Mining Techniques addresses all the major and latest techniques of data mining and data warehousing. It deals in detail with the latest algorithms for discovering association rules, decision trees, clustering, neural networks and genetic algorithms. The book contains the algorithmic details of different techniques such as A priori, Pincer-search, Dynamic Itemset Counting, FP-Tree growth, SLIQ, SPRINT, BOAT, CART, RainForest, BIRCH, CURE, BUBBLE, ROCK, STIRR, PAM, CLARANS, DBSCAN, GSP,...

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasets...

Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through...

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain...