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We have devised a predominantly Naive Bayes method to classify the optical/IRmatches to X-ray sources detected by Chandra in the Cygnus OB2 association intoforeground, member, and background objects. We employ a variety of X-ray,optical, and infrared characteristics to construct likelihoods using trainingsets defined by well-measured sources. Combinations of optical photometry fromSDSS (riz) and IPHAS (riHa), IR magnitudes from UKIDSS and 2MASS (JHK), X-rayquantiles and hardness ratios, and estimates of extinction Av are used tocompute the relative probabilities that a given source belongs to one of theclasses. We use Principal Component Analysis of photometric magnitudecombinations to isolate the best axes for classification. We incorporatemeasurement errors into the classification. We evaluate the accuracy of theclassification by inspection and reclassify a number of sources based on IRmagnitudes, presence of disks, and X-ray spectral hardness. We also considersystematic errors due to extinction. We find that about 6100 objects areassociation members, 1400 are background, and 500 are foreground objects. Theoverall classification accuracy is 95%.

Classification of Chandra X-ray Sources in Cygnus OB2