| Interface | Description |
|---|---|
| PerformanceEvaluator<ObjectType,DataType,ResultType> |
The
PerformanceEvaluator class defines the functionality of some
object with regards to some data. |
| SupervisedPerformanceEvaluator<InputType,TargetType,EstimateType,ResultType> |
The
SupervisedPerformanceEvaluator interface extends the
PerformanceEvaluator interface for performance evaluations of
supervised machine learning algorithms where the target type is evaluated
against the estimated type produced by the evaluator. |
| Class | Description |
|---|---|
| AbstractSupervisedPerformanceEvaluator<InputType,TargetType,EstimateType,ResultType> |
The
AbstractSupervisedPerformanceEvaluator class contains an
abstract implementation of the SupervisedPerformanceEvaluator class. |
| AnytimeBatchLearnerValidationPerformanceReporter<DataType,ObjectType> |
A performance reporter for a validation set.
|
| 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. |
| 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. |
| 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. |
| 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. |