Pichara, K; Protopapas, P.; Kim, D.-W.; Marquette, J B; Tisserand, Patrick
We present a new classification method for quasar identification in the EROS-2 and MACHO data sets based on a boosted version of a random forest classifier. We use a set of variability features including parameters of a continuous autoregressive model. We prove that continuous autoregressive parameters are very important discriminators in the classification process. We create two training sets (one for EROS-2 and one for MACHO data sets) using known quasars found in the Large Magellanic Cloud...[Show more]
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