MATLAB File Help: prtClusterGmm |
prtClusterGmm Gaussian mixture model clustering object CLUSTER = prtClusterGmm returns a GMM clustering object. CLUSTER = prtClusterGmm(PROPERTY1, VALUE1, ...) constructs a prtClassFld object CLASSIFIER with properties as specified by PROPERTY/VALUE pairs. A prtClusterGmm object inherits all properties from the abstract class prtCluster. In addition is has the following properties: nClusters - Number of cluster centers to learn A prtClusterGmm clustering algorithm trains a prtRvGmm random variable on training data, and at run time, the clustering algorithm outputs the posterior probability of any particular point being drawn from one of the nClusters Guassian components. A prtClusterGmm object inherits the TRAIN, RUN, CROSSVALIDATE and KFOLDS methods from prtAction. It also inherits the PLOT method from prtCluster. Example: ds = prtDataGenUnimodal % Load a data set clusterAlgo = prtClusterGmm; % Create a clustering object clusterAlgo.nClusters = 2; % Set the number of clusters % Set the internal decision rule to be MAP. Not required for % clustering, but necessary to plot the results. clusterAlgo.internalDecider = prtDecisionMap; clusterAlgo = clusterAlgo.train(ds); % Train plot(clusterAlgo); % Plot the trained object
Superclasses | prtCluster |
Sealed | false |
Construct on load | false |
prtClusterGmm | Gaussian mixture model clustering object |
clusterCenters | The cluster centers |
dataSet | The training prtDataSet, only stored if verboseStorage is true. |
dataSetSummary | Structure that summarizes prtDataSet. |
gmmRv | The Gaussian mixture model found during training |
includesDecision | Flag indicating if result includes a decision |
internalDecider | Optional prtDecider object for making decisions |
isCrossValidateValid | True |
isSupervised | False |
isTrained | Indicates if prtAction object has been trained. |
nClusters | The number of clusters |
name | GMM Clustering |
nameAbbreviation | GMMCluster |
showProgressBar | |
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 of the prtCluster 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. |