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J/MNRAS/427/2917
  Classification of Hipparcos variables (Rimoldini+, 2012)
ReadMe+ftp
2012MNRAS.427.2917R
Similar Catalogs
Post annotation 		img(gal)
1.J/MNRAS/427/2917/table2(c)Training set of Hipparcos variable stars (3881 rows)
2.J/MNRAS/427/2917/ptypes(c)Predicted of Hipparcos unsolved variables (tables 4 and 5 of paper) (6051 rows)
3.J/MNRAS/427/2917/tablec1Full random forest prediction probability arrays (6051 rows)
4.J/MNRAS/427/2917/tablec2Full multi-stage Bayesian nets prediction probability arrays (6051 rows)

Simple ConstraintList Of Constraints
 
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Column  Constraint Explain   (UCD)
  (ALL)recno  Record number assigned by the VizieR team. Should Not be used for identification. (meta.record)
   (ALL)HIP   [1/120404] Hipparcos number (meta.id;meta.main)
  (1+2)V-I mag Reddened V-I colour index in Cousins' system, as provided by ESA (1997) (Note 1)   (phot.color;em.opt.V;em.opt.I)
  (1+2)Skew  Unbiased skewness of the distribution of HIP magnitudes (Skewness) (Note 2)   (stat.fit.param)
  (1+2)logAmp [mag] Decadic logarithm of the difference between the faintest and the brightest values of the light-curve model (LogAmplitude) (Note 3)   (stat.value;arith.diff)
  (1+2)logPer [d] Decadic logarithm of the period (LogPeriod) (Note 4)   (time.period)
  (1+2)MAG mag Absolute magnitude in the Hipparcos band (AbsoluteMag) (Note 5)   (phot.mag;em.opt.V)
  (1+2)logFAP [-] [,0] Decadic logarithm of the probability that the maximum peak in the Lomb-Scargle periodogram (Scargle 1982ApJ...263..835S) is due to noise rather than the true signal (Note 6)   (stat.fit.param)
  (1+2)logP2P [-] Decadic logarithm of the point-to-point scatter of the time series (LogP2PscatterFoldedRaw) (Note 7)   (stat.fit.param)
  (1+2)logQSOvar [-] Decadic logarithm of the reduced chi-square of the source variability with respect to a parametrized QSO variance model (Note 8)   (stat.fit.chi2)
  (1+2)logScRaw [-] Decadic logarithm of the ratio between the median of absolute deviations from the median of the raw time series and the median of absolute values of the residual time series (logScatterRawRes) (Note 9)   (stat.fit.residual)

ALL cols		    
 (i)indexed column
  (1+2)logPlx [mas] Decadic logarithm of the parallax value as provided by ESA (2007) (LogParallax) (Note 10)   (pos.parallax.trig)
  (1+2)logSt [mag] Decadic logarithm of the unbiased standard deviation of the residual time series (logStdDevRes) (Note 11)   (stat.fit.residual)
  (1+2)logSVar [mag] Decadic logarithm of the average of absolute values of magnitude differences between all pairs of measurements separated by time-scales from 0.01 to 0.1 day (logShortVar) (Note 12)   (stat.fit.residual)
  (1+2)Sum  Ratio between the sum of squared residuals of the model from the raw data and the sum of squared deviations of the raw time series from its mean value (SumSqResRaw) (Note 13)   (stat.fit.residual)
  (1+2)|b| deg Absolute value of the Galactic latitude of the source position (AbsGLAT) (Note 14)   (pos.galactic.lat)
  (1+2)eFreq 10-4/d Error estimate of the derived frequency (FrequencyError) (Note 15)   (stat.error;em.freq)
  (1)Type (char) Variability type, only in table2 (Note 16)   (meta.note;src.var)
  (1+2)HIPdata (char) Display HIP data (meta.ref.url)
  (1+2)Simbad (char) ask the Simbad data-base about this object (meta.ref)
  (1+2)_RA deg (i) Positions from HIP2 reduction (Cat. I/311) (right ascension part) (pos.eq.ra;meta.main)
  (1+2)_DE deg (i) Positions from HIP2 reduction (Cat. I/311) (declination part) (pos.eq.dec;meta.main)
  (2)Set (char) Hipparcos sets from which the sources have been selected (HipparcosSet) (Note 17)   (phot.mag;em.opt.V)
  (2)HIPtype (char) Variability types as listed in HIP (HipparcosType) (Note 18)   (meta.code;src.var)

ALL cols		    
 (i)indexed column
  (2)VXtype (char) Variability types as listed in AAVSO (Note 19)   (meta.code;src.var)
  (2)RFtype (char) Variability types predicted by random forests (PredictedTypeRF) (grayed classes have a probability<50%) (Note 20)   (meta.code;src.var)
  (2)MBtype (char) Variability types predicted by a multi-stage methodology based on Bayesian networks (PredictedTypeMB) (grayed classes have a probability<50%) (Note 21)   (meta.code;src.var)
  (2)prRF   [0/1] Probability of the variability type predicted by random forests (ProbabilityRF) (stat.fit.goodness)
  (2)prMB   [0/1] Probability of the variability type predicted by a multi-stage methodology based on Bayesian networks (ProbabilityMB) (stat.fit.goodness)
  (3+4)IX  Probability of the source to be of type I_X, as predicted by random forests (ProbabilityI_X) (Note G1)   (stat.fit.goodness)
  (3+4)LPVP  Probability of the source to be of type LPV_P, as predicted by random forests (ProbabilityLPV_P) (Note G1)   (stat.fit.goodness)
  (3+4)LPVX  Probability of the source to be of type LPV_X, as predicted by random forests (ProbabilityLPV_X) (Note G1)   (stat.fit.goodness)
  (3+4)RS+BYP  Probability of the source to be of type RS+BY_P, as predicted by random forests (ProbabilityRS+BY_P) (Note G1)   (stat.fit.goodness)
  (3+4)RS+BYX  Probability of the source to be of type RS+BY_X, as predicted by random forests (ProbabilityRS+BY_X) (Note G1)   (stat.fit.goodness)
  (3+4)BE+GCASP  Probability of the source to be of type BE+GCAS_P as predicted by random forests (ProbabilityBE+GCAS_P) (Note G1)   (stat.fit.goodness)
  (3+4)BE+GCASX  Probability of the source to be of type BE+GCAS_X as predicted by random forests (ProbabilityBE+GCAS_X) (Note G1)   (stat.fit.goodness)
  (3+4)SPBP  Probability of the source to be of type SPB_P, as predicted by random forests (ProbabilitySPB_P) (Note G1)   (stat.fit.goodness)

ALL cols		    
 (i)indexed column
  (3+4)ACVP  Probability of the source to be of type ACV_P, as predicted by random forests (ProbabilityACV_P) (Note G1)   (stat.fit.goodness)
  (3+4)ACVX  Probability of the source to be of type ACV_X, as predicted by random forests (ProbabilityACV_X) (Note G1)   (stat.fit.goodness)
  (3+4)EAP  Probability of the source to be of type EA_P, as predicted by random forests (ProbabilityEA_P) (Note G1)   (stat.fit.goodness)
  (3+4)EAX  Probability of the source to be of type EA_X, as predicted by random forests (ProbabilityEA_X) (Note G1)   (stat.fit.goodness)
  (3+4)EBP  Probability of the source to be of type EB_P, as predicted by random forests (ProbabilityEB_P) (Note G1)   (stat.fit.goodness)
  (3+4)EWP  Probability of the source to be of type EW_P, as predicted by random forests (ProbabilityEW_P) (Note G1)   (stat.fit.goodness)
  (3+4)ELLP  Probability of the source to be of type ELL_P, as predicted by random forests (ProbabilityELL_P) (Note G1)   (stat.fit.goodness)
  (3+4)ACYGP  Probability of the source to be of type ACYG_P, as predicted by random forests (ProbabilityACYG_P) (Note G1)   (stat.fit.goodness)
  (3+4)ACYGX  Probability of the source to be of type ACYG_X, as predicted by random forests (ProbabilityACYG_X) (Note G1)   (stat.fit.goodness)
  (3+4)BCEPP  Probability of the source to be of type BCEP_P, as predicted by random forests (ProbabilityBCEP_P) (Note G1)   (stat.fit.goodness)
  (3+4)BCEPX  Probability of the source to be of type BCEP_X, as predicted by random forests (ProbabilityBCEP_X) (Note G1)   (stat.fit.goodness)
  (3+4)DCEPSP  Probability of the source to be of type DCEPS_P, as predicted by random forests (ProbabilityDCEPS_P) (Note G1)   (stat.fit.goodness)
  (3+4)DCEPP  Probability of the source to be of type DCEP_P, as predicted by random forests (ProbabilityDCEP_P) (Note G1)   (stat.fit.goodness)

ALL cols		    
 (i)indexed column
  (3+4)CEP(B)P  Probability of the source to be of type CEP(B)_P, as predicted by random forests (ProbabilityCEP(B)_P) (Note G1)   (stat.fit.goodness)
  (3+4)RRABP  Probability of the source to be of type RRAB_P, as predicted by random forests (ProbabilityRRAB_P) (Note G1)   (stat.fit.goodness)
  (3+4)RRCP  Probability of the source to be of type RRC_P, as predicted by random forests (ProbabilityRRC_P) (Note G1)   (stat.fit.goodness)
  (3+4)GDORP  Probability of the source to be of type GDOR_P, as predicted by random forests (ProbabilityGDOR_P) (Note G1)   (stat.fit.goodness)
  (3+4)GDORX  Probability of the source to be of type GDOR_X, as predicted by random forests (ProbabilityGDOR_X) (Note G1)   (stat.fit.goodness)
  (3+4)DSCTP  Probability of the source to be of type DSCT_P, as predicted by random forests (ProbabilityDSCT_P) (Note G1)   (stat.fit.goodness)
  (3+4)DSCTX  Probability of the source to be of type DSCT_X, as predicted by random forests (ProbabilityDSCT_X) (Note G1)   (stat.fit.goodness)
  (3+4)DSCTCP  Probability of the source to be of type DSCTC_P, as predicted by random forests (ProbabilityDSCTC_P) (Note G1)   (stat.fit.goodness)
  (3+4)DSCTCX  Probability of the source to be of type DSCTC_X, as predicted by random forests (ProbabilityDSCTC_X) (Note G1)   (stat.fit.goodness)
  (3+4)CWAP  Probability of the source to be of type CWA_P, as predicted by random forests (ProbabilityCWA_P) (Note G1)   (stat.fit.goodness)
  (3+4)CWBP  Probability of the source to be of type CWB_P, as predicted by random forests (ProbabilityCWB_P) (Note G1)   (stat.fit.goodness)
  (3+4)SXARIP  Probability of the source to be of type SXARI_P, as predicted by random forests (ProbabilitySXARI_P) (Note G1)   (stat.fit.goodness)
  (3+4)RVP  Probability of the source to be of type RV_P, as predicted by random forests (ProbabilityRV_P) (Note G1)   (stat.fit.goodness)

ALL cols		    
 (i)indexed column
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