MATLAB File Help: prtRegressLslr
 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
    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.
    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 =;   % 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)
See also
Class Details
Superclasses prtRegress
Sealed false
Construct on load false
Constructor Summary
prtRegressLslr prtRegresLslr Least squares regression object 
Property Summary
beta Regression weights estimated via least squares linear regression 
dataSet The training prtDataSet, only stored if verboseStorage is true.  
dataSetSummary Structure that summarizes prtDataSet. 
isCrossValidateValid True 
isSupervised True 
isTrained Indicates if prtAction object has been trained. 
name Least Squares Linear Regression 
nameAbbreviation LSLR 
plotOptions Plotting Options 
rss Resisudal sum of the squared error 
standardizedResiduals Standardized residuals 
t Measuer of the importance of each weight 
userData User specified data 
verboseStorage Specifies whether or not to store the training prtDataset. 
Method Summary
  crossValidate Cross validate prtAction using prtDataSet and cross validation keys. 
  get get the object properties 
  kfolds Perform K-folds cross-validation of prtAction 
  optimize Optimize action parameter by exhaustive function maximization. 
  plot Plot the prtRegress object 
  run Run a prtAction object on a prtDataSet object. 
  set set the object properties 
  train Train a prtAction object using training a prtDataSet object.