- We will send in 10–14 business days.
/images/books/7644372/9781312841017.jpg)
- Author: Jeffrey Strickland
- Publisher: Lulu.com
- ISBN-10: 131284101X
- ISBN-13: 9781312841017
- Format: 15.2 x 22.9 x 3 cm, hardcover
- Language: English
- SAVE -10% with code: EXTRA
Reviews
Description
This book is about predictive analytics. Yet, each chapter could easily be handled by an entire volume of its own. So one might think of this a survey of predictive modeling. A predictive model is a statistical model or machine learning model used to predict future behavior based on past behavior. In order to use this book, one should have a basic understanding of mathematical statistics - it is an advanced book. Some theoretical foundations are laid out but not proven, but references are provided for additional coverage. Every chapter culminates in an example using R. R is a free software environment for statistical computing and graphics. You may download R, from a preferred CRAN mirror at http: //www.r-project.org/. The book is organized so that statistical models are presented first (hopefully in a logical order), followed by machine learning models, and then applications: uplift modeling and time series. One could use this a textbook with problem solving in R-but there are no "by-hand" exercises.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 18d.03:31:57
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Jeffrey Strickland
- Publisher: Lulu.com
- ISBN-10: 131284101X
- ISBN-13: 9781312841017
- Format: 15.2 x 22.9 x 3 cm, hardcover
- Language: English English
This book is about predictive analytics. Yet, each chapter could easily be handled by an entire volume of its own. So one might think of this a survey of predictive modeling. A predictive model is a statistical model or machine learning model used to predict future behavior based on past behavior. In order to use this book, one should have a basic understanding of mathematical statistics - it is an advanced book. Some theoretical foundations are laid out but not proven, but references are provided for additional coverage. Every chapter culminates in an example using R. R is a free software environment for statistical computing and graphics. You may download R, from a preferred CRAN mirror at http: //www.r-project.org/. The book is organized so that statistical models are presented first (hopefully in a logical order), followed by machine learning models, and then applications: uplift modeling and time series. One could use this a textbook with problem solving in R-but there are no "by-hand" exercises.
Reviews