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You're reading from Mastering Machine Learning with R, Second Edition Advanced prediction, algorithms, and learning methods with R 3.x

Product type Paperback

Published in Apr 2017

Publisher Packt

ISBN-13 9781787287471

Length 420 pages

Edition 2nd Edition

Languages

Concepts

Machine Learning

Author (1):

Cory Lesmeister

View More author details

Table of Contents (17) Chapters

Preface

1. A Process for Success FREE CHAPTER

2. Linear Regression - The Blocking and Tackling of Machine Learning

3. Logistic Regression and Discriminant Analysis

4. Advanced Feature Selection in Linear Models

5. More Classification Techniques - K-Nearest Neighbors and Support Vector Machines

6. Classification and Regression Trees

7. Neural Networks and Deep Learning

8. Cluster Analysis

9. Principal Components Analysis

10. Market Basket Analysis, Recommendation Engines, and Sequential Analysis

11. Creating Ensembles and Multiclass Classification

12. Time Series and Causality

13. Text Mining

14. R on the Cloud

15. R Fundamentals

16. Sources

Sources

Granger, G.W.J., Newbold, P., (1974), Spurious Regressions in Econometrics, Journal of Econometrics, 1974 (2), 111-120

Hechenbichler, K., Schliep, K.P., (2004), Weighted k-Nearest-Neighbors and Ordinal Classification, Institute for Statistics, Sonderforschungsbereich 386, Paper 399. http://epub.ub.uni-muenchen.de/

Hinton, G.E., Salakhutdinov, R.R., (2006), Reducing the Dimensionality of Data with Neural Networks, Science, August 2006, 313(5786):504-7

James, G., Witten, D., Hastie, T., Tisbshirani, R. (2013), An Introduction to Statistical Learning, 1st ed. New York: Springer

Kodra, E., (2011), Exploring Granger Causality Between Global Average Observed Time Series of Carbon Dioxide and Temperature, Theoretical and Applied Climatology, Vol. 104 (3), 325-335

Natekin, A., Knoll, A., (2013), Gradient Boosting Machines, a Tutorial, Frontiers in Neurorobotics, 2013; 7-21. https://www.ncbi.nlm...

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Authors (1)

Lesmeister

Cory Lesmeister has over fourteen years of quantitative experience and is currently a senior data scientist for the advanced analytics team at Cummins, Inc. in Columbus, Indiana. He has spent 16 years at Eli Lilly and Company in sales, market research, Lean Six Sigma, marketing analytics, and new product forecasting. He also has several years of experience in the insurance and banking industries, both as a consultant and as a manager of marketing analytics. A former US Army active duty and reserve officer, Cory was stationed in Baghdad, Iraq, in 2009. Here, he served as the strategic advisor to the 29,000-person Iraqi Oil Police, succeeding where others failed by acquiring and delivering promised equipment to help the country secure and protect its oil infrastructure. He has a BBA in aviation administration from the University of North Dakota and a commercial helicopter license.

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