A DataDistribution defines an unsupervised learning problem. More...
#include <shark/Data/DataDistribution.h>
Public Member Functions | |
| virtual | ~DataDistribution () |
| Virtual destructor. | |
| virtual void | draw (InputType &input) const =0 |
| Generates a single pair of input and label. | |
| InputType | operator() () |
| UnlabeledData< InputType > | generateDataset (std::size_t size, std::size_t maximumBatchSize) const |
| Generates a data set with samples from from the distribution. | |
| UnlabeledData< InputType > | generateDataset (std::size_t size) const |
| Generates a data set with samples from from the distribution. | |
A DataDistribution defines an unsupervised learning problem.
Definition at line 57 of file DataDistribution.h.
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inlinevirtual |
Virtual destructor.
Definition at line 61 of file DataDistribution.h.
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pure virtual |
Generates a single pair of input and label.
| input | the generated input |
Implemented in shark::NormalDistributedPoints, and shark::ImagePatches.
Referenced by shark::DataDistribution< InputType >::generateDataset(), and shark::DataDistribution< InputType >::operator()().
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inline |
Generates a data set with samples from from the distribution.
| size | the number of samples in the dataset |
Definition at line 93 of file DataDistribution.h.
References shark::DataDistribution< InputType >::generateDataset().
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inline |
Generates a data set with samples from from the distribution.
| size | the number of samples in the dataset |
| maximumBatchSize | the maximum size of a batch |
Definition at line 79 of file DataDistribution.h.
References shark::createUnlabeledDataFromRange(), and shark::DataDistribution< InputType >::draw().
Referenced by shark::DataDistribution< InputType >::generateDataset().
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inline |
Definition at line 69 of file DataDistribution.h.
References shark::DataDistribution< InputType >::draw().