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Mastering Predictive Analytics with R

You're reading from   Mastering Predictive Analytics with R Master the craft of predictive modeling by developing strategy, intuition, and a solid foundation in essential concepts

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781783982806
Length 414 pages
Edition 1st Edition
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Toc

Table of Contents (13) Chapters Close

Preface 1. Gearing Up for Predictive Modeling 2. Linear Regression FREE CHAPTER 3. Logistic Regression 4. Neural Networks 5. Support Vector Machines 6. Tree-based Methods 7. Ensemble Methods 8. Probabilistic Graphical Models 9. Time Series Analysis 10. Topic Modeling 11. Recommendation Systems Index

Predicting atmospheric gamma ray radiation


In order to study boosting in action, in this section we'll introduce a new prediction problem from the field of atmospheric physics. More specifically, we will analyze the patterns made by radiation on a telescope camera in order to predict whether a particular pattern came from gamma rays leaking into the atmosphere, or from regular background radiation.

Gamma rays leave distinctive elliptical patterns and so we can create a set of features to describe these. The data set we will use is the MAGIC Gamma Telescope data set, hosted by the UCI Machine Learning repository at http://archive.ics.uci.edu/ml/datasets/MAGIC+Gamma+Telescope. Our data consists of 19,020 observations of the following attributes:

Column name

Type

Definition

FLENGTH

Numerical

The major axis of the ellipse (mm)

FWIDTH

Numerical

The minor axis of the ellipse (mm)

FSIZE

Numerical

Logarithm to the base ten of the sum of the content of all pixels in the camera photo

FCONC...

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