See: Description
| Class | Description |
|---|---|
| DelayFunction<DataType> |
Delays the input and returns the input from the parameterized number of
samples previous.
|
| FeatureHashing |
Implements a function that applies vector feature hashing.
|
| LinearRegressionCoefficientExtractor |
Takes a sampled sequence of equal-dimension vectors as input and computes
the linear regression coefficients for each dimension in the vectors.
|
| MultivariateDecorrelator |
Decorrelates a data using a mean and full or diagonal covariance matrix.
|
| MultivariateDecorrelator.DiagonalCovarianceLearner |
The
DiagonalCovarianceLearner class implements a BatchLearner
object for a MultivariateDecorrelator. |
| MultivariateDecorrelator.FullCovarianceLearner |
The
FullCovarianceLearner class implements a BatchLearner
object for a MultivariateDecorrelator. |
| RandomSubspace |
Selects a random subspace from the given vector, which is a random set of
indices.
|
| StandardDistributionNormalizer |
The
StandardDistributionNormalizer class implements a normalization
method where a real value is converted onto a standard distribution. |
| StandardDistributionNormalizer.Learner |
The
Learner class implements a BatchLearner object for
a StandardDistributionNormalizer. |