shark::UnlabeledData< InputT > Class Template Reference
Data set for unsupervised learning. More...
#include <shark/Data/Dataset.h>
Inheritance diagram for shark::UnlabeledData< InputT >:
Public Types | |
| typedef element_type | InputType |
| typedef detail::SharedContainer< InputT > | InputContainer |
| Public Types inherited from shark::Data< InputT > | |
| typedef batch_type & | batch_reference |
| typedef batch_type const & | const_batch_reference |
| typedef Batch< element_type >::reference | element_reference |
| typedef Batch< element_type >::const_reference | const_element_reference |
| typedef std::vector< std::size_t > | IndexSet |
| typedef boost::iterator_range< detail::DataElementIterator< Data< InputT > > > | element_range |
| typedef boost::iterator_range< detail::DataElementIterator< Data< InputT > const > > | const_element_range |
| typedef detail::BatchRange< Data< InputT > > | batch_range |
| typedef detail::BatchRange< Data< InputT > const > | const_batch_range |
Public Member Functions | |
| UnlabeledData () | |
| Constructor. More... | |
| UnlabeledData (Data< InputT > const &points) | |
| Construction from data. More... | |
| UnlabeledData (std::size_t size, element_type const &element, std::size_t batchSize=base_type::DefaultBatchSize) | |
| Construction with size and a single element. More... | |
| UnlabeledData (std::size_t numBatches) | |
| Create an empty set with just the correct number of batches. More... | |
| UnlabeledData (UnlabeledData const &container, std::vector< std::size_t > batchSizes) | |
| Construct a dataset with different batch sizes. it is a copy of the other dataset. More... | |
| UnlabeledData | operator= (Data< InputT > const &data) |
| we allow assignment from Data. More... | |
| UnlabeledData & | inputs () |
| Access to the base_type class as "inputs". More... | |
| UnlabeledData const & | inputs () const |
| Access to the base_type class as "inputs". More... | |
| UnlabeledData | splice (std::size_t batch) |
| Splits the container in two independent parts. The left part remains in the container, the right is stored as return type. More... | |
| virtual void | shuffle () |
| shuffles all elements in the entire dataset (that is, also across the batches) More... | |
| Public Member Functions inherited from shark::Data< InputT > | |
| BOOST_STATIC_CONSTANT (std::size_t, DefaultBatchSize=256) | |
| Defines the default batch size of the Container. More... | |
| bool | operator== (const Data< T > &rhs) |
| Two containers compare equal if they share the same data. More... | |
| bool | operator!= (const Data< T > &rhs) |
| Two containers compare unequal if they don't share the same data. More... | |
| const_element_range | elements () const |
| Returns the range of elements. More... | |
| element_range | elements () |
| Returns therange of elements. More... | |
| const_batch_range | batches () const |
| Returns the range of batches. More... | |
| batch_range | batches () |
| Returns the range of batches. More... | |
| std::size_t | numberOfBatches () const |
| Returns the number of batches of the set. More... | |
| std::size_t | numberOfElements () const |
| Returns the total number of elements. More... | |
| Shape const & | shape () const |
| Returns the shape of the elements in the dataset. More... | |
| Shape & | shape () |
| Returns the shape of the elements in the dataset. More... | |
| bool | empty () const |
| Check whether the set is empty. More... | |
| element_reference | element (std::size_t i) |
| const_element_reference | element (std::size_t i) const |
| batch_reference | batch (std::size_t i) |
| const_batch_reference | batch (std::size_t i) const |
| Data () | |
| Constructor which constructs an empty set. More... | |
| Data (std::size_t numBatches) | |
| Construct a dataset with empty batches. More... | |
| Data (std::size_t size, element_type const &element, std::size_t batchSize=DefaultBatchSize) | |
| Construction with size and a single element. More... | |
| void | read (InArchive &archive) |
| Read the component from the supplied archive. More... | |
| void | write (OutArchive &archive) const |
| Write the component to the supplied archive. More... | |
| virtual void | makeIndependent () |
| This method makes the vector independent of all siblings and parents. More... | |
| void | splitBatch (std::size_t batch, std::size_t elementIndex) |
| Data | splice (std::size_t batch) |
| Splits the container into two independent parts. The front part remains in the container, the back part is returned. More... | |
| void | append (Data const &other) |
| Appends the contents of another data object to the end. More... | |
| void | push_back (const_batch_reference batch) |
| void | repartition (Range const &batchSizes) |
| Reorders the batch structure in the container to that indicated by the batchSizes vector. More... | |
| std::vector< std::size_t > | getPartitioning () const |
| Creates a vector with the batch sizes of every batch. More... | |
| void | indexedSubset (IndexSet const &indices, Data &subset, Data &complement) const |
| Fill in the subset defined by the list of indices as well as its complement. More... | |
| Data | indexedSubset (IndexSet const &indices) const |
| Public Member Functions inherited from shark::ISerializable | |
| virtual | ~ISerializable () |
| Virtual d'tor. More... | |
| void | load (InArchive &archive, unsigned int version) |
| Versioned loading of components, calls read(...). More... | |
| void | save (OutArchive &archive, unsigned int version) const |
| Versioned storing of components, calls write(...). More... | |
| BOOST_SERIALIZATION_SPLIT_MEMBER () | |
Additional Inherited Members | |
| Protected Types inherited from shark::Data< InputT > | |
| typedef detail::SharedContainer< InputT > | Container |
| Protected Attributes inherited from shark::Data< InputT > | |
| Container | m_data |
| data More... | |
| Shape | m_shape |
| shape of a datapoint More... | |
Detailed Description
template<class InputT>
class shark::UnlabeledData< InputT >
Data set for unsupervised learning.
The UnlabeledData class is basically a standard Data container with the special interpretation of its data point being "inputs" to a learning algorithm.
The documentation for this class was generated from the following file:
- include/shark/Data/Dataset.h