| Interface | Description |
|---|---|
| CostFunction<EvaluatedType,CostParametersType> |
The CostFunction interface defines the interface to evaluate some object to
determine its cost.
|
| DifferentiableCostFunction |
The
DifferentiableCostFunction is a cost function that can
be differentiated. |
| ParallelizableCostFunction |
Interface describing a cost function that can (largely) be computed in
parallel.
|
| SupervisedCostFunction<InputType,TargetType> |
A type of CostFunction normally used in supervised-learning applications.
|
| Class | Description |
|---|---|
| AbstractCostFunction<EvaluatedType,CostParametersType> |
Partial implementation of CostFunction.
|
| AbstractParallelizableCostFunction |
Partial implementation of the ParallelizableCostFunction
|
| AbstractSupervisedCostFunction<InputType,TargetType> |
Partial implementation of SupervisedCostFunction
|
| ClusterDistortionMeasure<DataType,ClusterType extends Cluster<DataType>> |
Computes the objective measure for a clustering algorithm, based on the
internal "distortion" of each cluster.
|
| EuclideanDistanceCostFunction |
The EuclideanDistanceCostFunction class implements a CostFunction that
calculates the Euclidean distance the given Vectorizable and the goal
vector.
|
| KolmogorovSmirnovDivergence<DataType extends java.lang.Number> |
CostFunction that induces a CDF that most-closely resembles the
target distribution according to the Kolmogorov-Smirnov (K-S) test.
|
| MeanL1CostFunction |
Cost function that evaluates the mean 1-norm error (absolute value of
difference) weighted by a sample "weight" that is embedded in each sample.
|
| MeanSquaredErrorCostFunction |
The MeanSquaredErrorCostFunction implements a cost function for functions
that take as input a vector and return a vector.
|
| NegativeLogLikelihood<DataType> |
CostFunction for computing the maximum likelihood
(because we are minimizing the negative of the log likelihood)
|
| ParallelClusterDistortionMeasure<DataType,ClusterType extends Cluster<DataType>> |
A parallel implementation of ClusterDistortionMeasure.
|
| ParallelizedCostFunctionContainer |
A cost function that automatically splits a ParallelizableCostFunction
across multiple cores/processors to speed up computation.
|
| ParallelizedCostFunctionContainer.SubCostEvaluate |
Callable task for the evaluate() method.
|
| ParallelizedCostFunctionContainer.SubCostGradient |
Callable task for the computeGradient() method
|
| ParallelNegativeLogLikelihood<DataType> |
Parallel implementation of the NegativeLogLikleihood cost function
|
| ParallelNegativeLogLikelihood.NegativeLogLikelihoodTask<DataType> |
Task for computing partial log likelihoods
|
| SumSquaredErrorCostFunction |
This is the sum-squared error cost function
|
| SumSquaredErrorCostFunction.Cache |
Caches often-used values for the Cost Function
|
| SumSquaredErrorCostFunction.GradientPartialSSE |
Partial result from the SSE gradient computation
|