| MATLAB File Help: prtClassGlrt |
prtClassGlrt Generalized likelihood ratio test classifier CLASSIFIER = prtClassGlrt returns a Glrt classifier CLASSIFIER = prtClassGlrt(PROPERTY1, VALUE1, ...) constructs a prtClassGlrt object CLASSIFIER with properties as specified by PROPERTY/VALUE pairs. A prtClassGlrt object inherits all properties from the abstract class prtClass. In addition is has the following properties: rvH0 - A prtRvMvn object representing hypothesis 0 rvH1 - A prtRvMvn object representing hypothesis 1 A prtClassGlrt object inherits the TRAIN, RUN, CROSSVALIDATE and KFOLDS methods from prtAction. It also inherits the PLOT method from prtClass. Example: testDataSet = prtDataGenUniModal; % Create some test and trainingDataSet = prtDataGenUniModal; % training data classifier = prtClassGlrt; % Create a classifier classifier = classifier.train(trainingDataSet); % Train classifier.plot; classified = classifier.run(testDataSet); subplot(2,1,1); classifier.plot; subplot(2,1,2); [pf,pd] = prtScoreRoc(classified,testDataSet); h = plot(pf,pd,'linewidth',3); title('ROC'); xlabel('Pf'); ylabel('Pd');
| Superclasses | prtClass |
| Sealed | false |
| Construct on load | false |
| prtClassGlrt | Generalized likelihood ratio test classifier |
| dataSet | The training prtDataSet, only stored if verboseStorage is true. |
| dataSetSummary | Structure that summarizes prtDataSet. |
| internalDecider | Optional prtDecider object for making decisions |
| isCrossValidateValid | True |
| isNativeMary | False |
| isSupervised | True |
| isTrained | Indicates if prtAction object has been trained. |
| name | Generalized likelihood ratio test |
| nameAbbreviation | GLRT |
| rvH0 | Mean and variance of H0 |
| rvH1 | Mean and variance of H1 |
| showProgressBar | |
| twoClassParadigm | Whether the classifier retures one output (binary) or two outputs (m-ary) when there are only two unique class labels |
| userData | User specified data |
| verboseStorage | Specifies whether or not to store the training prtDataset. |
| 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 output confidence of a prtClass 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. |