Uses of Class
gov.sandia.cognition.learning.performance.AbstractSupervisedPerformanceEvaluator

Packages that use AbstractSupervisedPerformanceEvaluator

Package	Description
gov.sandia.cognition.learning.function.cost	Provides cost functions.
gov.sandia.cognition.learning.performance	Provides performance measures.
gov.sandia.cognition.learning.performance.categorization	Provides performance measures for categorizers.

Uses of AbstractSupervisedPerformanceEvaluator in gov.sandia.cognition.learning.function.cost

Subclasses of AbstractSupervisedPerformanceEvaluator in gov.sandia.cognition.learning.function.cost

Modifier and Type	Class and Description
class	AbstractParallelizableCostFunction Partial implementation of the ParallelizableCostFunction
class	AbstractSupervisedCostFunction<InputType,TargetType> Partial implementation of SupervisedCostFunction
class	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.
class	MeanSquaredErrorCostFunction The MeanSquaredErrorCostFunction implements a cost function for functions that take as input a vector and return a vector.
class	ParallelizedCostFunctionContainer A cost function that automatically splits a ParallelizableCostFunction across multiple cores/processors to speed up computation.
class	SumSquaredErrorCostFunction This is the sum-squared error cost function

Uses of AbstractSupervisedPerformanceEvaluator in gov.sandia.cognition.learning.performance

Subclasses of AbstractSupervisedPerformanceEvaluator in gov.sandia.cognition.learning.performance

Modifier and Type	Class and Description
class	MeanAbsoluteErrorEvaluator<InputType> The MeanAbsoluteError class implements a method for computing the performance of a supervised learner for a scalar function by the mean absolute value between the target and estimated outputs.
class	MeanSquaredErrorEvaluator<InputType> The MeanSquaredError class implements the method for computing the performance of a supervised learner for a scalar function by the mean squared between the target and estimated outputs.
class	MeanZeroOneErrorEvaluator<InputType,DataType> The MeanZeroOneErrorEvaluator class implements a method for computing the performance of a supervised learner by the mean number of incorrect values between the target and estimated outputs.
class	RootMeanSquaredErrorEvaluator<InputType> The RootMeanSquaredErrorEvaluator class implements a method for computing the performance of a supervised learner for a scalar function by the root mean squared error (RMSE or RSE) between the target and estimated outputs.

Uses of AbstractSupervisedPerformanceEvaluator in gov.sandia.cognition.learning.performance.categorization

Subclasses of AbstractSupervisedPerformanceEvaluator in gov.sandia.cognition.learning.performance.categorization

Modifier and Type	Class and Description
class	ConfusionMatrixPerformanceEvaluator<InputType,CategoryType> A performance evaluator that builds a confusion matrix.
static class	DefaultBinaryConfusionMatrix.PerformanceEvaluator<InputType> An implementation of the SupervisedPerformanceEvaluator interface for creating a DefaultBinaryConfusionMatrix.