Methodology for Automated Supervised Classification of Light Curves in the CoRoT Exoplanet Database

The exploration of the large databases currently produced by large scale ground-based surveys and space to missions requires the use of automated methods. We present an automated supervised classification method for large datasets containing light curves of variable stars. The methodology was developed in preparation of the CoRoT mission, but is more widely applicable. The classifiers are currently being applied to the data, measured in the CoRoT Exoplanet programme. Here, we give a brief overview of the results and the changes we have made to optimize the classification performance. A detailed analysis of the complete classification results is still ongoing.