Patent ID: 11934464
Assignee: MULTIVERSE COMPUTING S.L.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. The method for performing unsupervised clustering according to claim 1, wherein the cost function is:, H
  =
  
   
    1
    2
   
   ⁢
   
    
     ∑
     
      i
      ,
      
       j
       =
       1
      
     
     N
    
    
     
      (
      
       δ
       
        
         m
         i
        
        ⁢
        
         m
         j
        
       
      
      )
     
     ⁢
     
      (
      
       
        
         d
         ⁡
         (
         
          
           x
           i
          
          ,
          
           x
           j
          
         
         )
        
        α
       
       +
       
        λ
        ⁢
        
         d
         ⁡
         (
         
          
           x
           i
          
          ,
          
           c
           s
          
         
         )
        
       
      
      )
     
     ⁢
     
      (
      
       1
       -
       
        f
        i
       
      
      )
     
     ⁢
     
      (
      
       1
       -
       
        f
        j
       
      
      )
     
    
   
  
 

with:
xi being a data point of the data set, and xj being a different data point,
N being the number of data points in the data set,
δmimj being equal to 1 where both data points xi and xj are located in the same label, and 0 where they are located in different labels, mi being the label in which data point xi is located, and mj being the label in which data point xj is located,
m being the number of labels in which the data points will be clustered,
d(xi, xj) being the distance between data points xi and xj,
d(xi, cs) being the distance between data point xi and cs, cs being a centroid position of the label s in which data point xi is located, the centroid position being the average position of all the data points pertaining to the same label s,
fi being the probability of data point xi belonging to label s,
α being a data dependent hyperparameter of the cost function accounting for the relative importance of the distance between data points, and
λ being a data dependent hyperparameter of the cost function accounting for the relative importance of the distance between centroid position and data point.