| 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. |