Statistical And Machine-learning Data Mining, T... Page

: The book includes SAS subroutines that can be converted to other programming languages, making it highly applicable for practitioners.

: New content covers emerging and niche topics, including the rise of data science, market share estimation , and share of wallet modeling without survey data.

The book focuses heavily on techniques that start where traditional statistical data mining stops, such as the patented . Notable topics include: Statistical and Machine-Learning Data Mining, T...

: Some critics have noted a limited literature review and a lack of dedicated exercise sections for students. Others suggest that further discussion on high-dimensional data analysis would add value. Core Content & Methodologies

Professional reviewers and academics emphasize the book's blend of theory and "common sense". : The book includes SAS subroutines that can

: Experts from Harvard and Arizona State University highlight its "nitty-gritty, step-by-step" approach, describing it as a "valuable resource" for both novice and experienced data scientists.

: It features a user-friendly version of text mining that does not require an advanced background in natural language processing (NLP). Critical Perspectives and Expert Reviews Notable topics include: : Some critics have noted

: Reviewers from Technometrics note the book is well-written with numerous worked examples based on real-life datasets.