MATLAB File Help: prtPreProcMinMaxRows |
prtPreProcMinMaxRows Minimize and maximize all rows of the data MINMAX = prtPreProcMinMaxRows creates a min/max rows pre processing object. A prtPreProcMinMaxRows object linearly scales the input observations so that each row (observation) has a minimum of 0 and a maximum of 1. prtPreProcMinMaxRows has no user settable properties. A prtPreProcMinMaxRows object also inherits all properties and functions from the prtAction class. Note for two-dimensional data sets, min/max rows will result in all observations taking values 0 or 1. Example: dataSet = prtDataGenIris; % Load a data set dataSet = dataSet.retainFeatures(1:3); % Retain the first 3 features logDisc = prtPreProcMinMaxRows; % Create the pre processing % object minmax = logDisc.train(dataSet); % Train dataSetNew = minmax.run(dataSet); % Run % Plot subplot(2,1,1); plot(dataSet); title('Original Data'); subplot(2,1,2); plot(dataSetNew); title('MinMaxRows Data');
Superclasses | prtPreProc |
Sealed | false |
Construct on load | false |
prtPreProcMinMaxRows | Minimize and maximize all rows of the data |
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 | MinMax Rows |
nameAbbreviation | MMR |
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. |