Patent ID: 11960521
Assignee: nan
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 2:
3. The text classification method based on feature selection according to claim 2, wherein a calculation formula of the word frequency adjustment parameter α(t,cj) is as follows:, α
   ⁡
   (
   
    t
    ,
    
     c
     j
    
   
   )
  
  =
  
   
    N
    n
   
   ×
   
    
     tf
     ⁡
     (
     
      t
      ,
      
       c
       i
      
     
     )
    
    
     
      
       ∑
        
      
      
       i
       =
       1
      
      n
     
     ⁢
     
      tf
      ⁡
      (
      
       t
       ,
       
        c
        i
       
      
      )
     
    
   
  
 

where N represents the total number of all texts in the training set, n represents the number of documents containing the feature word t in the text set, tf(t,ci) represents the number of occurrences in the text of the category ci, Σi=1Ntf(t,ci) represents the number of all the occurrences in the documents of all categories, the word frequency adjustment parameter α(t,ci) represents calculating a ratio of the number of word frequencies of the feature word in each category to the total number of word frequencies of the feature item in all categories, and the larger value α(t,ci) represents that the feature word appears in a certain category of the text set more frequently and the ability to discriminate the corresponding categories is stronger;
a calculation formula of the intra-category position parameter β is as follows:, β
   j
  
  =
  
   
    1
    m
   
   ⁢
   
    
     ∑
     
      j
      =
      1
     
     m
    
     
    
     
      [
      
       
        
         tf
         j
        
        (
        t
        )
       
       -
       
        
         1
         m
        
        ⁢
        
         
          ∑
          
           i
           =
           1
          
          m
         
          
         
          
           tf
           j
          
          (
          t
          )
         
        
       
      
      ]
     
     2
    
   
  
 

which is normalized as:, β
  =
  
   1
   -
   
    
     β
     j
    
    
     
      
       
        ∑
         
       
       
        j
        =
        1
       
       m
      
      ⁢
      
       β
       j
       2
      
     
    
   
  
 

where m represents the total number of the categories, and tfj(t) represents a word frequency of the feature word tin the category j;
a calculation formula of the negative correlation correction factor γ is as follows:, γ
  =
  
   
    N
    ⁡
    (
    
     t
     ,
     
      c
      i
     
    
    )
   
   -
   
    
     
      
       ∑
        
      
      
       j
       =
       1
      
      n
     
     ⁢
     
      N
      ⁡
      (
      
       t
       ,
       
        c
        i
       
      
      )
     
    
    m
   
  
 

where N(t,ci) is the number of texts in which the feature word t appears in the category cj, Σj=1nN(t,ci) is the total number of texts in which the feature word t appears in the text set, and m is the number of categories.