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See:
Description
| Class Summary | |
|---|---|
| AbstractBootstrappingValidation | This validation operator performs several bootstrapped samplings (sampling with replacement) on the input set and trains a model on these samples. |
| BatchXValidation |
BatchXValidation encapsulates a cross-validation process. |
| BootstrappingValidation | This validation operator performs several bootstrapped samplings (sampling with replacement) on the input set and trains a model on these samples. |
| FixedSplitValidationChain | A FixedSplitValidationChain splits up the example set at a fixed point into a training and test set and evaluates the model (linear sampling). |
| IteratingPerformanceAverage | This operator chain performs the inner operators the given number of times. |
| RandomSplitValidationChain |
A RandomSplitValidationChain splits up the example set into a
training and test set and evaluates the model. |
| RandomSplitWrapperValidationChain | This operator evaluates the performance of feature weighting algorithms including feature selection. |
| SplitValidationOperator | A FixedSplitValidationChain splits up the example set at a fixed point into a training and test set and evaluates the model (linear sampling). |
| Tools | Tools class for validation operators. |
| ValidationChain | Abstract superclass of operator chains that split an ExampleSet into
a training and test set and return a performance vector. |
| WeightedBootstrappingValidation | This validation operator performs several bootstrapped samplings (sampling with replacement) on the input set and trains a model on these samples. |
| WrapperValidationChain | This operator evaluates the performance of feature weighting algorithms including feature selection. |
| WrapperXValidation | This operator evaluates the performance of feature weighting and selection algorithms. |
| XValidation |
XValidation encapsulates a cross-validation process. |
Operators for estimation of the performance which can be achieved by learning schemes (and other predictive operators). Provides several forms of cross ans split validation for both learning schemes and methods (validate a wrapper approach).
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