DSC (Discrete Source Classifier)
DSC is currently designed along modular lines, with several different classification algorithms working in parallel on different types of data. Probabilistic outputs from individual subclassifiers will be combined into a final output. The subclassifiers are;
- Photometric classifier, working on BPRP spectra. Based on a support vector machine (SVM)
- Position G magnitude classifier. Provides a prior based on source magnitude and sky position. Based on a Kernel density estimate of the sky distributions.
- Astrometric Classifier. Classifies based on proper motion and parallax. Based on a Gaussian mixture model.
- Variability classifier. Classify sources based on a photometric time series. Will be based on a structure function analysis and probably a mixture model. Not yet implemented.