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 |
|---|---|---|
|
|
Numerical |
The major axis of the ellipse (mm) |
|
|
Numerical |
The minor axis of the ellipse (mm) |
|
|
Numerical |
Logarithm to the base ten of the sum of the content of all pixels in the camera photo |
|
|