SHOGUN  6.1.3
Namespaces | Classes
shogun::internal Namespace Reference

Namespaces

 mmd
 

Classes

class  Block
 Class that holds a block feature. A block feature is a shallow copy of an underlying (non-owning) feature object. In its constructor, it increases the refcount of the original object (since it has to be alive as long as the block is alive) and it decreases the refcount of the original object in destructor. More...
 
class  BlockwiseDetails
 Class that holds block-details for the data-fetchers. There are one instance of this class per fetcher. More...
 
class  DataManager
 Class DataManager for fetching/streaming test data block-wise. It can handle data coming from multiple sources. The number of data sources is represented by the num_distributions parameter in the constructor of the data manager. It can handle heterogenous data sources, and it can stream multiple blocks per burst, as the computation would require. The size of the blocks and the number of blocks to be fetched per burst can be set externally. More...
 
struct  GoodnessOfFitTest
 Meta test-type for goodness-of-fit test. More...
 
struct  IndependenceTest
 Meta test-type for independence test. More...
 
class  NextSamples
 class NextSamples is the return type for next() call in DataManager. If there are no more samples (from any one of the distributions), an empty instance of NextSamples is supposed to be returned. This can be verified from the caller by calling the empty() method. Otherwise, always a get() call with appropriate index would give the samples from that distribution. If an inappropriate index is provided, e.g. get(2) for a two-sample test, a runtime exception is thrown. More...
 
struct  OneDistributionTest
 Meta test-type for 1-distribution statistical tests. More...
 
struct  ThreeDistributionTest
 Meta test-type for 3-distribution statistical tests. More...
 
struct  TwoDistributionTest
 Meta test-type for 2-distribution statistical tests. More...
 
struct  TwoSampleTest
 Meta test-type for two-sample test. More...
 

SHOGUN Machine Learning Toolbox - Documentation