Classification of Type II Cepheids

Required packages:

astropy, pandas, upsilon, seaborn, pickle, urllib, sklearn, FATS -- available on https://github.com/isadoranun/FATS

Folders and Files

time_series_analysis

The file "LX_Cyg.ipynb" is a tutorial showing how to plot the raw data, a periodogram, and phase plot.

feature_extraction

This folder goes over the process of extracting features from the raw data and storing them in an SQL database. The file "feature_extraction.ipynb" is using a Python 2.7 kernel. It is important to note that every other .ipynb file in this repository is using a Python 3.x kernel.

classification

This folder goes over the steps involved to make the classifier "voting_ensemble_without_colour.pickle". This includes data visualization, outlier detection and removal, feature scaling, principal component analysis, tuning the hyper-parameters of a model, and evaluating the goodness of the classifier.

classifier_finished

This folder demonstrates how to use the classifier. Place the raw data files in the folder "Time_Series". Each raw data file must include the columns time, magnitude, and error which are separated by a space. Then run scripts "1. feature_extraction.ipynb" and "2. classification.ipynb", respectively.

machine_learning_notes.pdf

These notes are intended to provide some intuition and mathematical background to the machine learning techniques that were used to make the classifier.