Practical Predictive Modeling Applications

Practical Predictive Modeling Applications is an essential guide for individuals looking to apply predictive models effectively in practical scenarios. This book covers a wide range of topics related to predictive modeling, including non-linear models, regression models, and regression trees, using the popular R programming language. Whether you're a data scientist, analyst, or researcher, this resource equips you with the knowledge and tools needed to build and deploy predictive models for real-world applications. With a focus on practicality, it offers insights into the implementation and usage of these models, making it an invaluable reference for mastering the art of predictive modeling.

Subjects / Topics

Mathematics and Statistics, Statistics for Life Sciences, Medicine, Health Sciences, Statistics and Computing/Statistics Programs, Statistics, general

Keywords Covered

Model, Non-Linear, Predictive Models, R, Regression Models, Regression Trees

Pages – 590