Data Mining for Business Analytics: Concepts, Techniques, and
Applications with JMP Pro(R) presents an applied and interactive
approach to data mining.
Featuring hands-on applications with JMP Pro(R), a statistical package
from the SAS Institute, the book
uses engaging, real-world examples to build a theoretical and practical
understanding of key data mining methods, especially predictive models
for classification and prediction. Topics include data visualization,
dimension reduction techniques, clustering, linear and logistic
regression, classification and regression trees, discriminant analysis,
naive Bayes, neural networks, uplift modeling, ensemble models, and time
series forecasting.
Data Mining for Business Analytics: Concepts, Techniques, and
Applications with JMP Pro(R) also includes:
- Detailed summaries that supply an outline of key topics at the
beginning of each chapter
- End-of-chapter examples and exercises that allow readers to expand
their comprehension of the presented material
- Data-rich case studies to illustrate various applications of data
mining techniques
- A companion website with over two dozen data sets, exercises and case
study solutions, and slides for instructors www.dataminingbook.com
Data Mining for Business Analytics: Concepts, Techniques, and
Applications with JMP Pro(R) is an excellent textbook for advanced
undergraduate and graduate-level courses on data mining, predictive
analytics, and business analytics. The book is also a one-of-a-kind
resource for data scientists, analysts, researchers, and practitioners
working with analytics in the fields of management, finance, marketing,
information technology, healthcare, education, and any other data-rich
field.
