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Practical Machine Learning Cookbook

You're reading from   Practical Machine Learning Cookbook Supervised and unsupervised machine learning simplified

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781785280511
Length 570 pages
Edition 1st Edition
Languages
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Author (1):
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Atul Tripathi Atul Tripathi
Author Profile Icon Atul Tripathi
Atul Tripathi
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Table of Contents (15) Chapters Close

Preface 1. Introduction to Machine Learning FREE CHAPTER 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...

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