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Practical Machine Learning Cookbook

You're reading from  Practical Machine Learning Cookbook

Product type Book
Published in Apr 2017
Publisher Packt
ISBN-13 9781785280511
Pages 570 pages
Edition 1st Edition
Languages
Author (1):
Atul Tripathi Atul Tripathi
Profile icon Atul Tripathi

Table of Contents (21) Chapters

Practical Machine Learning Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Introduction to Machine Learning 2. Classification 3. Clustering 4. Model Selection and Regularization 5. Nonlinearity 6. Supervised Learning 7. Unsupervised Learning 8. Reinforcement Learning 9. Structured Prediction 10. Neural Networks 11. Deep Learning 12. Case Study - Exploring World Bank Data 13. Case Study - Pricing Reinsurance Contracts 14. Case Study - Forecast of Electricity Consumption

Generalized additive models - measuring the household income of New Zealand


An income survey provides a snapshot of income levels for people and households. It gives median and average weekly income from most sources. There are income comparisons across different population groups. Income is only received intermittently, whereas consumption is smoothed over time. As a consequence, it is reasonable to expect that consumption is more directly related to current living standards than current income, at least for short reference periods.

Getting ready

In order to perform shrinkage methods, we will be using a dataset collected on the New Zealand Census 2013.

Step 1 - collecting and describing data

The nzcensus package contains demographic values of New Zealand that are more than 60 in number. These values have been accumulated at the level of mesh block, area unit, territorial authority, and regional council.

How to do it...

Let's get into the details.

Step 2 - exploring data

The first step is to load...

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