In this paper we present a methodology for automating theclassification of spectrally resolved observations of multiple emissionlines with the Atacama Large Millimeter/submillimeter Array (ALMA).Molecules in planetary atmospheres emit or absorb different wavelengthsof light thereby providing a unique signature for each species. ALMAdata were taken from interferometric observations of Titan made be-tween UT 2012 July 03 23:22:14 and 2012 July 04 01:06:18 as part ofALMA project 2011.0.00319.S. We first employed a greedy set cover algorithm to identify the most probable molecules that would reproducethe set of frequencies with respective flux greater than 3σaway from themean. We then selected a subset of those molecules as present in theatmosphere by specifying a selection threshold and one of two selectionmetrics. Our model was able to correctly classify 100% of previously dis-covered molecules in Titan’s atmosphere from this data, including EthylCyanide as reported by Cardiner et al. (2015)[2]. One molecule, Formalde-hyde, was identified in both selection metrics that was not previouslyrecorded in the atmosphere. The results of our methodology allow for astreamlined approach for molecule classification and anomaly detectionin planetary atmospheres