MALT: Machine Learning for Transients

MALT is a classification pipeline based on the paper “Classification of Multiwavelength Transients with Machine Learning” by Sooknunan et al. (2018). It is a framework which allows the user to classify time series data. The user is free to choose the interpolation technique, feature extraction method, and the machine learning classifier to use.

The default pipeline is shown below. It uses Gaussian processes to interpolate the data, a wavelet feature extraction method and a random forest classifier.