prtRegresLslr  Least squares regression object
 
    REGRESS = prtRegressLslr returns a prtRegressLslr object
 
    REGRESS = prtRegressLslr(PROPERTY1, VALUE1, ...) constructs a
    prtRegressGP object REGRESS with properties as specified by
    PROPERTY/VALUE pairs.
  
    A prtRegressLslr object inherits all properties from the prtRegress
    class. In addition, it has the following properties:
 
    beta                   - The regression weights
    t                      - A measure of feature importance
    rss                    - The residual sum of squares
    standardizedResiduals  -  The standardized residuals
 
  
    A prtRegressionLslr object inherits the PLOT method from the
    prtRegress object, and the TRAIN, RUN, CROSSVALIDATE and KFOLDS
    methods from the prtAction object.
 
    Example:
    
    x = [1:.5:10]';                % Create a linear, noisy data set.
    y = 2*x + 3 + randn(size(x));
    dataSet = prtDataSetRegress;  % Create a prtDataSetRegress object
    dataSet= dataSet.setX(x);
    dataSet = dataSet.setY(y);
    dataSet.plot;                    % Display data
    reg = prtRegressLslr;            % Create a prtRegressRvm object
    reg = reg.train(dataSet);        % Train the prtRegressRvm object
    reg.plot();                      % Plot the resulting curve
    dataSetOut = reg.run(dataSet);   % Run the regressor on the data
    hold on;
    plot(dataSet.getX,dataSetOut.getX,'k*') % Plot, overlaying the
                                            % fitted points with the 
                                            % curve and original data
  legend('Regression line','Original Points','Fitted points',0)