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Table 1:
Mathematical Notation.
Dimensions (number of features) p 
Data , point n, feature i 
Masks  
Cluster label k 
Total number of clusters K 
Mixture weight, cluster mean, covariance  
Probability density function of the multivariate gaussian distribution  
Total number of data points N 
Number of points for which feature i is masked  
Noise mean for feature i  
Noise variance for feature i  
Virtual features (random variable)  
Mean of virtual feature  
  
Variance of virtual feature  
Log likelihood of in cluster k  
Set of data points assigned to cluster k  
Subset of for which feature i is fully masked  
Dimensions (number of features) p 
Data , point n, feature i 
Masks  
Cluster label k 
Total number of clusters K 
Mixture weight, cluster mean, covariance  
Probability density function of the multivariate gaussian distribution  
Total number of data points N 
Number of points for which feature i is masked  
Noise mean for feature i  
Noise variance for feature i  
Virtual features (random variable)  
Mean of virtual feature  
  
Variance of virtual feature  
Log likelihood of in cluster k  
Set of data points assigned to cluster k  
Subset of for which feature i is fully masked  
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