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You're reading from  Practical Machine Learning Cookbook

Product typeBook
Published inApr 2017
Reading LevelIntermediate
PublisherPackt
ISBN-139781785280511
Edition1st Edition
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Author (1)
Atul Tripathi
Atul Tripathi
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Atul Tripathi

Atul Tripathi has spent more than 11 years in the fields of machine learning and quantitative finance. He has a total of 14 years of experience in software development and research. He has worked on advanced machine learning techniques, such as neural networks and Markov models. While working on these techniques, he has solved problems related to image processing, telecommunications, human speech recognition, and natural language processing. He has also developed tools for text mining using neural networks. In the field of quantitative finance, he has developed models for Value at Risk, Extreme Value Theorem, Option Pricing, and Energy Derivatives using Monte Carlo simulation techniques.
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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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Practical Machine Learning Cookbook
Published in: Apr 2017Publisher: PacktISBN-13: 9781785280511

Author (1)

author image
Atul Tripathi

Atul Tripathi has spent more than 11 years in the fields of machine learning and quantitative finance. He has a total of 14 years of experience in software development and research. He has worked on advanced machine learning techniques, such as neural networks and Markov models. While working on these techniques, he has solved problems related to image processing, telecommunications, human speech recognition, and natural language processing. He has also developed tools for text mining using neural networks. In the field of quantitative finance, he has developed models for Value at Risk, Extreme Value Theorem, Option Pricing, and Energy Derivatives using Monte Carlo simulation techniques.
Read more about Atul Tripathi