000002797 001__ 2797
000002797 005__ 20160701171711.0
000002797 0247_ $$2DOI$$a10.1007/978-1-4614-3323-1_11
000002797 037__ $$aASTROimport-954
000002797 100__ $$aDubath, P.
000002797 245__ $$aHipparcos Variable Star Detection and Classification Efficiency
000002797 260__ $$c2012
000002797 520__ $$aA complete periodic star extraction and classification scheme is set up and tested with the Hipparcos catalog. The efficiency of each step is derived by comparing the results with prior knowledge coming from the catalog or from the literature. A combination of two variability criteria is applied in the first step to select 17,006 variability candidates from a complete sample of 115,152 stars. Our candidate sample turns out to include 10,406 known variables (i.e., 90% of the total of 11,597) and 6,600 contaminating constant stars. A random forest classification is used in the second step to extract 1,881 (82%) of the known periodic objects while removing entirely constant stars from the sample and limiting the contamination of nonperiodic variables to 152 stars (7.5%). The confusion introduced by these 152 nonperiodic variables is evaluated in the third step using the results of the Hipparcos periodic star classification presented in a previous study [Dubath et al. (Mon Not R Astron Soc May:651, 2011)]. 
000002797 700__ $$a Lecoeur-Taïbi, I.
000002797 700__ $$a Rimoldini, L.
000002797 700__ $$a Süveges, M.
000002797 700__ $$a Blomme, J.
000002797 700__ $$a López, M.
000002797 700__ $$a Sarro, L. M.
000002797 700__ $$a De Ridder, J.
000002797 700__ $$a Cuypers, J.
000002797 700__ $$a Guy, L.
000002797 700__ $$a Nienartowicz, K.
000002797 700__ $$a Jan, A.
000002797 700__ $$a Beck, M.
000002797 700__ $$a Mowlavi, N.
000002797 700__ $$a De Cat, P.
000002797 700__ $$a Lebzelter, T.
000002797 700__ $$a Eyer, L.
000002797 773__ $$c117$$pAstrostatistics and Data Mining$$y2012
000002797 85642 $$ahttp://esoads.eso.org/abs/2012adm..book..117D
000002797 905__ $$apublished in
000002797 980__ $$aNONREF