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BootstrapTModel, TInput, TOutput Properties |
The BootstrapTModel, TInput, TOutput generic type exposes the following members.
Properties| Name | Description | |
|---|---|---|
 | B |
Gets or sets the number B of bootstrap samplings
to be drawn from the population dataset.
|
| DefaultValue |
Gets or sets a value to be used as the Loss in case the model throws
an exception during learning. Default is null (exceptions will not be ignored).
(Inherited from BaseSplitSetValidationTResult, TModel, TLearner, TInput, TOutput.) |
| Fit |
Gets or sets a LearnNewModelTLearner, TInput, TOutput, TModel function that can be used to create
new machine learning models using the current
learning algorithm.
(Inherited from BaseSplitSetValidationTResult, TModel, TLearner, TInput, TOutput.) |
| Learner |
Gets or sets a CreateLearnerFromSubsetTLearner, TInput, TOutput function
that can be used to create a TModel from a subset of the learning dataset.
(Inherited from BaseSplitSetValidationTResult, TModel, TLearner, TInput, TOutput.) |
| Loss |
Gets or sets a ComputeLossTOutput, TInfo function that can
be used to measure how far the actual model predictions were from the expected ground-truth.
(Inherited from BaseSplitSetValidationTResult, TModel, TLearner, TInput, TOutput.) |
| NumberOfSubsamples |
Gets or sets the number of samples to be drawn in each subsample. If
set to zero, all samples in the entire dataset will be selected.
|
| ParallelOptions |
Gets or sets the parallelization options for this algorithm.
(Inherited from ParallelLearningBase.) |
| SubSampleIndices |
Gets the bootstrap samples drawn from the population dataset as indices.
|
| Token |
Gets or sets a cancellation token that can be used
to cancel the algorithm while it is running.
(Inherited from ParallelLearningBase.) |
See Also