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PMM

PURPOSE ^

PMM Learning for boltzmann m/c

SYNOPSIS ^

function model = PMM( data, A )

DESCRIPTION ^

 PMM Learning for boltzmann m/c

 The Pseudo Moment Matching method to estimate parameters of a boltzmann m/c

 Inputs: 
          data: (N X V) matrix containing the data samples. 
                 N is the total number of samples and V is the total number of nodes                                         
                 Each node can take values from {+1,-1} or {0,1}.
             A: (V X V) adjacency matrix defining the graph structure
 Returns:
          model: (1X1) struct array with fields
                   N: the number of nodes
                   A: adjacency matrix                 
                   b: the biases  ( PL estimates )
                   w: the edge weights ( PL estimates )

 The node value representation ( +1/-1 or 0/1) intended by the user is detected from the training samples.       
 If using +1/-1, the data is first mapped to 0/1 and the model params are learned. 
 These learned params are then mapped back to the +1/-1 case.


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CROSS-REFERENCE INFORMATION ^

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