Applied Predictive Modeling
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Description
📈 Unlock predictive power with the pro’s playbook — don’t get left behind!
- AWARD WINNING PRACTICALITY - Winner of the prestigious 2014 Technometrics Ziegel Prize for outstanding applied methodology.
- BRIDGE THEORY AND PRACTICE - Balanced coverage of essential theory with actionable techniques for professional-grade models.
- CODE FIRST APPROACH WITH R - Leverage comprehensive, ready-to-run R scripts that accelerate your data science workflow.
- STAY AHEAD IN DATA SCIENCE - Tackle class imbalance, model tuning, and variable importance like a seasoned analyst.
- MASTER REAL WORLD PREDICTIVE MODELING - Dive into 20+ diverse datasets from pharma to concrete strength for hands-on learning.
Applied Predictive Modeling is a critically acclaimed, prize-winning textbook that expertly blends practical data science with foundational theory. Featuring over 20 real-world datasets and extensive R code, it guides advanced undergraduates, graduate students, and professionals through the entire predictive modeling pipeline—from preprocessing to model tuning—using modern regression and classification techniques. Ideal for those with basic R knowledge, this book is a must-have reference for mastering applied predictive analytics across diverse industries.
Specifications
| Best Sellers Rank | #1,015,576 in Books ( See Top 100 in Books ) #101 in Biostatistics (Books) #155 in Mathematical & Statistical Software |
| Customer Reviews | 4.6 4.6 out of 5 stars (326) |
| Dimensions | 6.4 x 1.5 x 9.3 inches |
| Edition | 2013th |
| ISBN-10 | 1461468485 |
| ISBN-13 | 978-1461468486 |
| Item Weight | 2.2 pounds |
| Language | English |
| Print length | 613 pages |
| Publication date | May 17, 2013 |
| Publisher | Springer |
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