| PLS2CrossValidationWithJackknife(ICrossValidationSubsets, Boolean, Boolean) Constructor |
Constructs a PLS2CrossValidationWithJackknife instance which uses the given subset
generator and the Nipals algorithm. No scaling and full model coefficients
will be used in the jackknife coefficient variance estimate computation.
No scaling will be done and full model coefficients will be used in the
jackknife coefficient variance estimate computation.
Namespace: CenterSpace.NMath.CoreAssembly: NMath (in NMath.dll) Version: 7.4
Syntax public PLS2CrossValidationWithJackknife(
ICrossValidationSubsets subsetGenerator,
bool scale,
bool useMean
)
Public Sub New (
subsetGenerator As ICrossValidationSubsets,
scale As Boolean,
useMean As Boolean
)
public:
PLS2CrossValidationWithJackknife(
ICrossValidationSubsets^ subsetGenerator,
bool scale,
bool useMean
)
new :
subsetGenerator : ICrossValidationSubsets *
scale : bool *
useMean : bool -> PLS2CrossValidationWithJackknife
Parameters
- subsetGenerator ICrossValidationSubsets
- Implementation of the ICrossValidationSubsets
interface that will be used to generate the training and testing subsets.
- scale Boolean
- If true, the learning X data for each subset is scaled
by dividing each variable by its sample standard deviation. The prediction
data is scaled by the same amount. Note that this will impact performance.
- useMean Boolean
- If true the mean of the coefficients computed
in the jackknife replicates will be used to compute variance estimates.
If false the full model coefficients will be used.
See Also