  The aim of this study is to distinguish genuine cosmic voids, found in a
galaxy catalog by the void finder ZOBOV-VIDE, from under-dense regions in a
Poisson distribution of objects. For this purpose, we perform two multivariate
analyses using the following physical void characteristics: volume, redshift,
density contrast, minimum density, contrast significance and number of member
galaxies of the void. The multivariate analyses are trained on a catalog of
voids obtained from a random Poisson distribution of points, used as
background, and a catalog of voids identified in a mock galaxy catalog, used as
signal. The classifications are then applied to voids extracted from the Data
Release 12 sample of Luminous Red Galaxies in the redshift range 0.45 $\leq$ z
$\leq$ 0.7 from the Sloan Digital Sky Survey Baryon Oscillation Spectroscopic
Survey (SDSS BOSS DR12 CMASS). Our results show that the resulting void catalog
is nearly free of contamination by Poisson noise. We also study the effect of
tracer sparsity and bias on the classification efficiencies.
