VizieR Online Data Catalog: outlier detection algorithm for SDSS galaxies (Baron+, 2017)

We have introduced an outlier detection algorithm that is based on an unsupervised implementation of RF. By construction, the algorithm learns the most important features of the data and their interconnections; it is completely general and can be applied to imaging data, time series and other spectroscopic objects as well. Out of 2355926 galaxies that compose the input sample, we chose 400 galaxies with the highest weirdness score. We find objects with unusual emission line ratios, and complex velocity structures, extremely red objects, objects with extremely strong absorption lines (i.e. sodium and Hα), galaxies which host supernovae, or have rare emission lines.

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