 | PLS |
Class PLS2 performs a Partial Least Squares (PLS) regression calculation
on a set of predictive and response values. The result is used to predict
response variable values.
Inheritance HierarchyNamespace: CenterSpace.NMath.Core
Assembly: NMath (in NMath.dll) Version: 7.4
SyntaxThe PLS2 type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | PLS2 | Default constructor. Calculator is set to the default. |
| PLS2(IPLS2Calc) | Constructs a PLS2 instance which uses the given calculator. |
| PLS2(DoubleMatrix, DoubleMatrix, Int32) | Constructs a PLS2 instance with the default calculator and performs a PLS2 calculation on the given data. |
| PLS2(IPLS2Calc, DoubleMatrix, DoubleMatrix, Int32) | Constructs a PLS2 instance with the given calculator and performs a PLS2 calculation on the given data. /// |
Properties| Name | Description | |
|---|---|---|
 | Calculator | Gets and sets the calculator. |
| IsGood | Whether the calculation was successful. |
| Message | Gets any message that may have been generated by the algorithm. For example, if the calculation is unsuccessful, the message indicate the reason. |
| NumComponents | Gets and sets the number of predictor variable components to use in the calculation. |
| X | Gets the predictor matrix. |
| Y | Gets the response matrix. |
Methods| Name | Description | |
|---|---|---|
| Calculate(DataFrame, DataFrame, Int32) | Calculates the partial least squares fit. |
| Calculate(DoubleMatrix, DoubleMatrix, Int32) | Calculates the partial least squares fit. |
| Clone | Creates a deep copy of this PLS2. |
| HotellingsT2 | Calculaties Hotelling's T2 statistic for each sample. T2 can be viewed as the squared distance from a samples projection into the subspace to the centroid of the subspace, or, more simply, the variation of the sample point within the model. |
| Predict(DoubleMatrix) | Predict the responses for a set of predictor values. |
| Predict(DoubleVector) | Calculates the predicted value of the response variable for the given value of the predictor variable. |
| QResiduals | Calculates the Q residuals for in sample in the model. The Q residual for a given sample is the distance between the sample and its projection in the subspace of the model. |
Fields| Name | Description | |
|---|---|---|
  | DEFAULT_CALCULATOR | Calculator to use when no specific calculator is specified. |
See Also