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Random forest automated supervised classification of Hipparcos periodic variable stars
We present an evaluation of the performance of an automatedclassification of the Hipparcos periodic variable stars into 26 types.The sub-sample with the most reliable variability types available in theliterature is used to train supervised algorithms to characterize thetype dependencies on a number of attributes. The most useful attributesevaluated with the random forest methodology include, in decreasingorder of importance, the period, the amplitude, the V-I colour index,the absolute magnitude, the residual around the folded light-curvemodel, the magnitude distribution skewness and the amplitude of thesecond harmonic of the Fourier series model relative to that of thefundamental frequency. Random forests and a multi-stage scheme involvingBayesian network and Gaussian mixture methods lead to statisticallyequivalent results. In standard 10-fold cross-validation (CV)experiments, the rate of correct classification is between 90 and 100per cent, depending on the variability type. The main mis-classificationcases, up to a rate of about 10 per cent, arise due to confusion betweenSPB and ACV blue variables and between eclipsing binaries, ellipsoidalvariables and other variability types. Our training set and thepredicted types for the other Hipparcos periodic stars are availableonline.
| Proper identification of RR Lyrae stars brighter than 12.5 mag
RR Lyrae stars are of great importance for investigations of Galacticstructure. However, a complete compendium of all RR-Lyraes in the solarneighbourhood with accurate classifications and coordinates does notexist to this day. Here we present a catalogue of 561 local RR-Lyraestars (V_max ≤ 12.5 mag) according to the magnitudes given in theCombined General Catalogue of Variable Stars (GCVS) and 16 fainter ones.The Tycho2 catalogue contains ≃100 RR Lyr stars. However, manyobjects have inaccurate coordinates in the GCVS, the primary source ofvariable star information, so that a reliable cross-identification isdifficult. We identified RR Lyrae from both catalogues based on anintensive literature search. In dubious cases we carried out photometryof fields to identify the variable. Mennessier & Colome (2002,A&A, 390, 173) have published a paper with Tyc2-GCVSidentifications, but we found that many of their identifications arewrong.
| Stars with the Largest Hipparcos Photometric Amplitudes
A list of the 2027 stars that have the largest photometric amplitudes inHipparcos Photometry shows that most variable stars are all Miras. Thepercentage of variable types change as a function of amplitude. Thiscompilation should also be of value to photometrists looking forrelatively unstudied, but large amplitude stars.
| The 74th Special Name-list of Variable Stars
We present the Name-list introducing GCVS names for 3153 variable starsdiscovered by the Hipparcos mission.
| Stromgren and H-beta photometry of stars earlier than G0 in 5 areas containing high latitude molecular clouds
Abstract image available at:http://adsabs.harvard.edu/cgi-bin/nph-bib_query?1989A&AS...80..127F&db_key=AST
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