Description:
Build models and perform predictions using the ridge regression method.
Syntax:
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   ridge(X, Y, learning_rate, iterations)  | 
  
  
   The function fits together matrix X and vector Y using the ridge regression method and returns model information that includes coefficient matrix and and intercept. The model information can act as parameter F in ridge(X’, F) to perform a fitting computation.  | 
  
 
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   ridge(X’, F)  | 
  
  
   The function fits together two matrices that have same number of columns – that is, perform predictions on another matrix X’ using model F, and returns a vector.  | 
  
 
Note:
MathCli external library function (See External Library Guide).
Parameter:
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   X  | 
  
  
   A matrix.  | 
  
 
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   Y  | 
  
  
   A vector having the same number of rows as matrix X.  | 
  
 
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   learning_rate  | 
  
  
   Learning rate that is a decimal between 0 and 1; default value is 0.01.  | 
  
 
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   iterations  | 
  
  
   Number of iterations; default is 1000.  | 
  
 
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   X’  | 
  
  
   A matrix that has same number of columns as matrix X.  | 
  
 
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   F  | 
  
  
   The return result of ridge (X, Y, learning_rate, iterations).  | 
  
 
Return value:
Matrix/Vector
Example:
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  | 
  
  
   A  | 
  
  
   
  | 
  
 ||||
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   1  | 
  
  
   [[1.1,1.1],[1.4,1.5],[1.7,1.8],[1.7,1.7],[1.8,1.9],[1.8,1.8],[1.9,1.8],[2.0,2.1],[2.3,2.4],[2.4,2.5]]  | 
  
  
   
  | 
  
 ||||
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   2  | 
  
  
   [16.3,16.8,19.2,18,19.5,20.9,21.1,20.9,20.3,22]  | 
  
  
   
  | 
  
 ||||
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   3  | 
  
  
   =ridge(A1,A2,0.01,10000)  | 
  
  
  
 Fit A1 and A2 together using ridge regression method and return coefficient matrix A3(1) and intercept A3(2) .  | 
  
 ||||
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   4  | 
  
  
   =ridge(A1,A3)  | 
  
  
  
 Perform prediction on A1 using model A3; the result can be compared with actual values in A2.  |