| MATLAB File Help: prtPreProcLogDisc |
prtPreProcLogDisc Histogram equalization processing LOGDISC = prtPreProcLogDisc creates a logistic discriminant pre processing object. A prtPreProcLogDisc object processes the input data so that each feature dimension is scaled between 0 and 1 to best match the data set class labels. prtPreProcLogDisc has no user settable properties. A prtPreProcLogDisc object also inherits all properties and functions from the prtAction class Example: dataSet = prtDataGenUnimodal; % Load a data set logDisc = prtPreProcLogDisc; % Create a pre processing object logDisc = logDisc.train(dataSet); % Train dataSetNew = logDisc.run(dataSet); % Run % Plot subplot(2,1,1); plot(dataSet); title('Original Data'); subplot(2,1,2); plot(dataSetNew); title('LogDisc Data');
| Superclasses | prtPreProcClass |
| Sealed | false |
| Construct on load | false |
| prtPreProcLogDisc | Allow for string, value pairs |
| 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. |
| name | 'Logistic Discriminant' |
| nameAbbreviation | LogDisc |
| 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. | |
| run | Run a prtAction object on a prtDataSet object. | |
| set | set the object properties | |
| train | Train a prtAction object using training a prtDataSet object. |