Description:
Pulsars are a rare type of Neutron star that produce radio emission detectable here on Earth. They are of considerable scientific interest as probes of space-time, the interstellar medium, and states of matter. Machine learning tools are now being used to automatically label pulsar candidates to facilitate rapid analysis. In particular, classification systems are widely adopted, which treat the candidate data sets as binary classification problems.
Attribute information:
Each candidate is described by 8 continuous variables and a single class variable. The first four are simple statistics obtained from the integrated pulse profile (folded profile). This is an array of continuous variables that describe a longitude-resolved version of the signal that has been averaged in both time and frequency. The remaining four variables are similarly obtained from the DM-SNR curve. These are summarised below:
1. Mean of the integrated profile.
2. Standard deviation of the integrated profile.
3. Excess kurtosis of the integrated profile.
4. Skewness of the integrated profile.
5. Mean of the DM-SNR curve.
6. Standard deviation of the DM-SNR curve.
7. Excess kurtosis of the DM-SNR curve.
8. Skewness of the DM-SNR curve.
9. Class
Descriptions courtesy of Ustav Murarka:
Integrated Pulse Profile: Each pulsar produces a unique pattern of pulse emission known as its pulse profile. It is like a fingerprint of the pulsar. It is possible to identify pulsars from their pulse profile alone. But the pulse profile varies slightly in every period. This makes the pulsar hard to detect. This is because their signals are non-uniform and not entirely stable overtime. However, these profiles do become stable, when averaged over many thousands of rotations.
DM-SNR Curve: Radio waves emitted from pulsars reach earth after traveling long distances in space which is filled with free electrons. Since radio waves are electromagnetic in nature, they interact with these electrons, this interaction results in slowing down of the wave. The important point is that pulsars emit a wide range of frequencies, and the amount by which the electrons slow down the wave depends on the frequency. Waves with higher frequency are sowed down less as compared to waves with higher frequency. i.e. lower frequencies reach the telescope later than higher frequencies. This is called dispersion.
Dataset Summary:
17,898 total examples.
1,639 positive examples.
16,259 negative examples.
Example
Example from Prof. Anna Scaife at the University of Manchester, UK- https://as595.github.io/classification/
Source: (https://archive.ics.uci.edu/ml/datasets/HTRU2)
Dr. Robert Lyon
University of Manchester
School of Physics and Astronomy
Alan Turing Building
Manchester M13 9PL
United Kingdom
robert.lyon '' manchester.ac.uk
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