MATLAB File Help: prtPreProcPls |
prtPreProcPls Partial least squares PLS = prtPreProcPls creates a partial least-squares pre-processing object. PLS = prtPreProcPls('nComponents',N) constructs a prtPreProcPLS object PLS with nComponents set to the value N. A prtPreProcPls object has the following properites: nComponents - The number of principle componenets A prtPreProcPls object also inherits all properties and functions from the prtAction class Example: dataSet = prtDataGenFeatureSelection; % Load a data set pls = prtPreProcPls; % Create a prtPreProcPls Object pls = pls.train(dataSet); % Train dataSetNew = pls.run(dataSet); % Run % Plot plot(dataSetNew); title('PLS Projected Data');
Superclasses | prtPreProc |
Sealed | false |
Construct on load | false |
prtPreProcPls | Partial least squares |
dataSet | The training prtDataSet, only stored if verboseStorage is true. |
dataSetSummary | Structure that summarizes prtDataSet. |
isCrossValidateValid | True |
isSupervised | False |
isTrained | Indicates if prtAction object has been trained. |
nComponents | The number of Pls components |
name | Partial Least Squares |
nameAbbreviation | PLS |
projectionMatrix | Projection Matrix |
showProgressBar | |
userData | User specified data |
verboseStorage | Specifies whether or not to store the training prtDataset. |
xMeanVector | X means |
yMeanVector | Y means |
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. | |
run | Run a prtAction object on a prtDataSet object. | |
set | set the object properties | |
train | Train a prtAction object using training a prtDataSet object. |