prtDecisionBinarySpecifiedPd Decision object for a specified Pd
 
  prtDec = prtDecisionBinarySpecifiedPd creates a prtDecisionBinarySpecifiedPd
  object, which can be used find a decision threshold in a binary
  classification problem for a specific probability of detection Pd.
 
  A prtDecisionBinarySpecifiedPd has the following member:
 
  pd - The specified probability of detection, which must be between 0
  and 1.
 
  prtDecision objects are intended to be used either as members of
  prtAlgorithm or prtClass objects.
 
  Example 1:
 
  ds = prtDataGenBimodal;              % Load a data set
  classifier = prtClassKnn;            % Create a clasifier
  classifier = classifier.train(ds);   % Train the classifier
  yOutClassifier = classifier.run(ds); % Run the classifier
 
  % Construct a prtAlgorithm object consisting of a prtClass object and
  % a prtDecision object
  dec = prtDecisionBinarySpecifiedPd;
  dec.pd = .7;   % Set the desired probility of detection.
  algo = prtClassKnn + dec;
 
  algo = algo.train(ds);        % Train the algorithm
  yOutAlgorithm = algo.run(ds); % Run the algorithm
 
  % Plot and compare the results
  subplot(2,1,1); stem(yOutClassifier.getObservations); title('KNN Output');
  subplot(2,1,2); stem(yOutAlgorithm.getObservations); title('KNN + Decision Output');
 
  Example 2:
 
  ds = prtDataGenBimodal;              % Load a data set
  classifier = prtClassKnn;            % Create a clasifier
  classifier = classifier.train(ds);   % Train the classifier
 
  % Plot the trained classifier
  subplot(2,1,1); plot(classifier); title('KNN');
 
  % Set the classifiers internealDecider to be a prtDecsion object
  classifier.internalDecider = dec;
 
  classifier = classifier.train(ds); % Train the classifier
  subplot(2,1,2); plot(classifier); title('KNN + Decision');