Implements train/test data splitting: first 50% of original data for training, second 50% for testing, each (data)class split separately. More...

#include <data_splitter_5050.hpp>

Inheritance diagram for FST::Data_Splitter_5050< INTERVALCONTAINER, IDXTYPE >:

Public Types
typedef Clonable_Impl< Data_Splitter_5050, Data_Splitter< INTERVALCONTAINER, IDXTYPE >, CLONE_INHERIT, CLONE_INHERIT, CLONE_DEEP >	parent_impl
	implements stateless_clone(); clone/sharing_clone throw in Data_Splitter
Public Types inherited from FST::Data_Splitter< INTERVALCONTAINER, IDXTYPE >
typedef std::shared_ptr< INTERVALCONTAINER >	PIntervaller
	shared pointer to one class's list of train/test data intervals

Public Member Functions
	Data_Splitter_5050 (const Data_Splitter_5050 &dsp)
	copies configuration (this splitter is parameterless, so there is nothing else to copy)
virtual IDXTYPE	getNoOfSplits () const override
virtual std::ostream &	print (std::ostream &os) const override
	writes a human-readable identification of the splitter and its configuration; base default writes nothing
Public Member Functions inherited from FST::Clonable_Impl< Data_Splitter_5050< INTERVALCONTAINER, IDXTYPE >, Data_Splitter< INTERVALCONTAINER, IDXTYPE >, CLONE_INHERIT, CLONE_INHERIT, CLONE_DEEP >
Data_Splitter< INTERVALCONTAINER, IDXTYPE > *	clone () const override
	dispatches to the DEEP_KIND mechanism (default CLONE_DEEP: Derived's copy-constructor)
Data_Splitter< INTERVALCONTAINER, IDXTYPE > *	sharing_clone () const override
	dispatches to the SHARING_KIND mechanism (default CLONE_INHERIT: defers to Base, which throws by family convention)
Data_Splitter< INTERVALCONTAINER, IDXTYPE > *	stateless_clone () const override
	dispatches to the STATELESS_KIND mechanism (default CLONE_INHERIT: defers to Base, which throws by family convention)
Public Member Functions inherited from FST::Data_Splitter< INTERVALCONTAINER, IDXTYPE >
	Data_Splitter (const Data_Splitter &dsp)
	Deep-copies every class's TClassSplitter (own train/test interval lists, not shared with `dsp`).
void	assign (const unsigned int _clsidx, const PIntervaller _train, const PIntervaller _test)
	Registers class `_clsidx's` train/test interval lists (growing csplit as needed); the caller retains ownership via the shared pointers.
void	set_n (const unsigned int _clsidx, const IDXTYPE _n)
	Sets class `_clsidx's` pattern count, which getNoOfSplits() and the concrete prepare‍/splitClass hooks size their splits against (growing csplit as needed).
IDXTYPE	get_n (const unsigned int _clsidx) const
	the pattern count previously set for class `_clsidx` via set_n()
bool	makeFirstSplit ()
	Produces the first split: prepareFirstSplit(), then splitClassFirst() per class, then finishSplit().
bool	makeNextSplit ()
	Produces the next split: prepareNextSplit(), then splitClassNext() per class, then finishSplit().
Data_Splitter *	clone () const override
Data_Splitter *	sharing_clone () const override
Public Member Functions inherited from FST::Clonable
bool	is_clone () const
bool	is_sharing () const
	true if this instance is a sharing_clone() result (referencing, not owning, the source's structures)
bool	is_sharing_clone () const
	true if this instance is BOTH a clone and sharing – i.e. specifically a sharing_clone() result, not a clone()/stateless_clone() one

Protected Types
typedef Data_Splitter< INTERVALCONTAINER, IDXTYPE >	TCC
	alias for the Data_Splitter base, used by the per-class hook
Protected Types inherited from FST::Data_Splitter< INTERVALCONTAINER, IDXTYPE >
typedef std::shared_ptr< TClassSplitter >	PClassSplitter
	shared pointer to one class's TClassSplitter
typedef std::vector< PClassSplitter >::const_iterator	ClassIterator
	iterator over csplit, as passed to the per-class splitClassFirst()/splitClassNext() hooks

Protected Member Functions
virtual const char *	splitter_name () const override
	class name, used in error messages
virtual bool	prepareNextSplit () override
	advance split-sequence state; false = no more splits
virtual void	splitClassFirst (typename TCC::ClassIterator c, const unsigned int) override
	write first-split train/test intervals of class `cidx` (`c` is that class's entry in csplit)
Protected Member Functions inherited from FST::Data_Splitter< INTERVALCONTAINER, IDXTYPE >
void	assert_csplit () const
	DEBUG-only: asserts csplit is non-empty and every class has n>0 and non-null train/test lists.
virtual bool	prepareFirstSplit ()
	set up split-sequence state; false = no split can be made
virtual void	splitClassNext (ClassIterator c, const unsigned int cidx)
	write next-split train/test intervals of class `cidx` (a single-split splitter never gets here, since its prepareNextSplit() returns false)
virtual void	finishSplit ()
	post-loop state update shared by first/next split
Protected Member Functions inherited from FST::Clonable
void	set_cloned (const bool cloned=true)
	marks/unmarks this instance as a clone; call from clone()/stateless_clone() overrides (Clonable_Impl does this automatically)
void	set_sharing (const bool sharing=true)
	marks/unmarks this instance as sharing (see is_sharing())
void	set_sharing_cloned (const bool cloned=true, const bool sharing=true)
	sets both flags at once; call from sharing_clone() overrides (Clonable_Impl does this automatically)

Additional Inherited Members
Protected Attributes inherited from FST::Data_Splitter< INTERVALCONTAINER, IDXTYPE >
std::vector< PClassSplitter >	csplit
	one TClassSplitter per data class, indexed by class index; grown on demand by assign()/set_n()

Detailed Description

template<class INTERVALCONTAINER, typename IDXTYPE>
class FST::Data_Splitter_5050< INTERVALCONTAINER, IDXTYPE >

Implements train/test data splitting: first 50% of original data for training, second 50% for testing, each (data)class split separately.

Yields exactly one split. A class of odd size gives the extra sample to the TEST part (the train size is the size divided by two, rounded down).

Warning: The split is by position, not at random: it depends entirely on the order the samples happen to have in the file. Data sorted by anything that correlates with the class – or with a feature – produces two systematically different halves and a misleading accuracy estimate. Use Data_Splitter_RandomRandom or a cross-validation splitter when the ordering is not known to be arbitrary.

Examples: demo10.cpp, and demo52t.cpp.