The nearest neighbors (NNs) classifiers, especially the k-Nearest Neighbors (kNNs) algorithm, are among the simplest and yet most efficient classification rules and widely used in practice. It is a nonparametric method of pattern recognition. In this paper, k-Nearest Neighbors, one of the most commonly used machine learning methods, work in automatic classification of multi-wavelength astronomical objects. Through the experiment, we conclude that the running speed of the kNN classier is rather fast and the classification accuracy is up to 97.73%. As a result, it is efficient and applicable to discriminate active objects from stars and normal galaxies with this method. The classifiers trained by the kNN method can be used to solve the automated classification problem faced by astronomy and the virtual observatory (VO).
LI LiLi1,2,3, ZHANG YanXia1 & ZHAO YongHeng1 1 National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
1RXS J201607.0+251645 is identified as an eclipsing binary.We present preliminary observations in the V band with the 0.6-m telescope for three years and extensive observations in the V and R bands with the 0.8-m telescope for six nights,respectively.The light curve of the system is EB type.Five light minimum times were obtained and the orbital period of 0.388058d(±0.00044d) is determined.The photometric solution given by the 2003-version of the Wilson-Devinney program suggests that the binary is a semi-detached system with photometric mass ratio 0.895(±0.006),which is probably comprised of a G5 primary and an oversized K5 secondary.The less massive component has completely filled its Roche lobe,while the other one almost fills its Roche lobe with a filling factor of 93.4%.The system shows a varying O'Connell effect in its phase folded diagrams from 2005 to 2007,and is X-ray luminous with log LX/Lbol ～ -3.27.Possible mechanisms to account for these two phenomena are discussed.Finally,we infer that the binary may be in thermal oscillation or may evolve into a contact binary.
