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You're reading from  Learning Bayesian Models with R

Product typeBook
Published inOct 2015
Reading LevelBeginner
PublisherPackt
ISBN-139781783987603
Edition1st Edition
Languages
R
Concepts
Machine Learning
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Author (1)
Hari Manassery Koduvely
Hari Manassery Koduvely
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Hari Manassery Koduvely

Dr. Hari M. Koduvely is an experienced data scientist working at the Samsung R&D Institute in Bangalore, India. He has a PhD in statistical physics from the Tata Institute of Fundamental Research, Mumbai, India, and post-doctoral experience from the Weizmann Institute, Israel, and Georgia Tech, USA. Prior to joining Samsung, the author has worked for Amazon and Infosys Technologies, developing machine learning-based applications for their products and platforms. He also has several publications on Bayesian inference and its applications in areas such as recommendation systems and predictive health monitoring. His current interest is in developing large-scale machine learning methods, particularly for natural language understanding.
Read more about Hari Manassery Koduvely

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Exercises

  1. In this exercise, we will use the DBWorld e-mails dataset from the UCI Machine Learning repository to compare the relative performance of Naïve Bayes and BayesLogit methods. The dataset contains 64 e-mails from the DBWorld newsletter and the task is to classify the e-mails into either announcements of conferences or everything else. The reference for this dataset is a course by Prof. Michele Filannino (reference 5 in the References section of this chapter). The dataset can be downloaded from the UCI website at https://archive.ics.uci.edu/ml/datasets/DBWorld+e-mails#.

    Some preprocessing of the dataset would be required to use it for both the methods. The dataset is in the ARFF format. You need to download the foreign R package (http://cran.r-project.org/web/packages/foreign/index.html) and use the read.arff( ) method in it to read the file into an R data frame.

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Learning Bayesian Models with R
Published in: Oct 2015Publisher: PacktISBN-13: 9781783987603
© 2015 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Hari Manassery Koduvely

Dr. Hari M. Koduvely is an experienced data scientist working at the Samsung R&D Institute in Bangalore, India. He has a PhD in statistical physics from the Tata Institute of Fundamental Research, Mumbai, India, and post-doctoral experience from the Weizmann Institute, Israel, and Georgia Tech, USA. Prior to joining Samsung, the author has worked for Amazon and Infosys Technologies, developing machine learning-based applications for their products and platforms. He also has several publications on Bayesian inference and its applications in areas such as recommendation systems and predictive health monitoring. His current interest is in developing large-scale machine learning methods, particularly for natural language understanding.
Read more about Hari Manassery Koduvely

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