Use the multivariate dataset named Auto MPG from the UCI Machine Learning repository (reference 3 in the

*References*section of this chapter). The dataset can be downloaded from the website at https://archive.ics.uci.edu/ml/datasets/Auto+MPG. The dataset describes automobile fuel consumption in**miles per gallon**(**mpg**) for cars running in American cities. From the folder containing the datasets, download two files:`auto-mpg.data`

and`auto-mpg.names`

. The`auto-mpg.data`

file contains the data and it is in space-separated format. The`auto-mpg.names`

file has several details about the dataset, including variable names for each column. Build a regression model for the fuel efficiency, as a function displacement (*disp*), horse power (*hp*), weight (*wt*), and acceleration (*accel*), using both OLS and Bayesian GLM. Predict the values for mpg in the test dataset using both the OLS model and Bayesian GLM model (using the`bayesglm`

function). Find the**Root Mean Square Error**(**RMSE**) values for OLS and...

#### Learning Bayesian Models with R

##### By :

#### Learning Bayesian Models with R

##### By:

#### Overview of this book

Table of Contents (16 chapters)

Learning Bayesian Models with R

Credits

About the Author

About the Reviewers

www.PacktPub.com

Preface

Free Chapter

Introducing the Probability Theory

The R Environment

Introducing Bayesian Inference

Machine Learning Using Bayesian Inference

Bayesian Regression Models

Bayesian Classification Models

Bayesian Models for Unsupervised Learning

Bayesian Neural Networks

Bayesian Modeling at Big Data Scale

Index

Customer Reviews