Home > @BestDecisionStumpClassifier > computeOutputs.m

computeOutputs

PURPOSE ^

function [outs] = computeOutputs(cl, examples)

SYNOPSIS ^

function [outs, prop] = computeOutputs(cl, examples)

DESCRIPTION ^

 function [outs] = computeOutputs(cl, examples)
   computes the classification outputs for the given examples
 
   Inputs:
       cl : trained classifier
       examples : data instances (number of instance X number of features)

   Outputs:
       outs : predicted classes
       prob : probability of each instance to belong to predicted class

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function [outs, prop] = computeOutputs(cl, examples)
0002 % function [outs] = computeOutputs(cl, examples)
0003 %   computes the classification outputs for the given examples
0004 %
0005 %   Inputs:
0006 %       cl : trained classifier
0007 %       examples : data instances (number of instance X number of features)
0008 %
0009 %   Outputs:
0010 %       outs : predicted classes
0011 %       prob : probability of each instance to belong to predicted class
0012 
0013 if ~cl.isTrained
0014     error('Decision Tree Classifier is not trained');
0015 end
0016 
0017 %% Handle Cell Arrays
0018 if iscell(examples),
0019     examples = cell2mat(examples);
0020 end
0021 
0022 %%TODO: remove acc output
0023 acc = NaN;
0024 
0025 %% Compute Outs
0026 [outs, prop] = cl.trainedCl.predict(examples);
0027

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