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Hands-On Ensemble Learning with R

You're reading from Hands-On Ensemble Learning with R

Product type Book

Published in Jul 2018

Publisher Packt

ISBN-13 9781788624145

Pages 376 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Prabhanjan Narayanachar Tattar

Table of Contents (17) Chapters

Hands-On Ensemble Learning with R

Contributors

Preface

1. Introduction to Ensemble Techniques

2. Bootstrapping

3. Bagging

4. Random Forests

5. The Bare Bones Boosting Algorithms

6. Boosting Refinements

7. The General Ensemble Technique

8. Ensemble Diagnostics

9. Ensembling Regression Models

10. Ensembling Survival Models

11. Ensembling Time Series Models

12. What's Next?

Bibliography

Index

Core concepts and metrics

The visualization of the time series data has conveyed a similar story in all the examples, from Figure 1 to Figure 7. The trend and seasonality of the observations imply that the future values of the time series are dependent on the current values, and thus we can't assume that the observations are independent of each other. But what does this mean? To reiterate the point, consider the simpler uspop (US population) dataset, the third-right panel display of Figure 7. Here, we don't have a seasonal influence. Now, consider the census year 1900. The population at the next census is certainly not less than in the year 1890, and it is not well beyond the same number of the same year. A similar narrative holds for most time series; for example, if we are recording the maximum temperature of the day. Here, if today's maximum temperature is 42°C, the next day's maximum temperature is highly influenced by this number and it is almost completely ruled out that the next day...

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Authors (1)

Prabhanjan Narayanachar Tattar

Prabhanjan Narayanachar Tattar is a lead statistician and manager at the Global Data Insights & Analytics division of Ford Motor Company, Chennai. He received the IBS(IR)-GK Shukla Young Biometrician Award (2005) and Dr. U.S. Nair Award for Young Statistician (2007). He held SRF of CSIR-UGC during his PhD. He has authored books such as Statistical Application Development with R and Python, 2nd Edition, Packt; Practical Data Science Cookbook, 2nd Edition, Packt; and A Course in Statistics with R, Wiley. He has created many R packages.

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