Before revision:  SSCFlow explicitly utilizes the observed labels to facilitate the imputation and classification simultaneously by employing a semi-supervised algorithm to estimate the conditional probability density of missing values .
After revision:  SSCFlow explicitly utilizes the observed labels to facilitate the imputation and classification simultaneously by estimating the conditional distribution of incomplete instances with a novel semi-supervised algorithm to estimate the conditional probability density of missing values .