Stump Class Reference

#include <Stump.hh>

Inheritance diagram for Stump:

List of all members.

Classes
struct	stump_experience
Public Types
enum	splitTypes { ONLY, CUT }
Public Member Functions
void	buildStump ()
float	calcGainRatio (int dim, float val, int type, float I)
float	calcIforSet (const std::vector< stump_experience * > &instances)
float	calcIofP (float *P, int size)
void	compareSplits (float gainRatio, int dim, float val, int type, int *nties, float *bestGainRatio, int *bestDim, float *bestVal, int *bestType)
int	findMatching (const std::vector< stump_experience * > &instances, int dim, int val, int minConf)
float	getConf (const std::vector< float > &input)
virtual Stump *	getCopy ()
void	implementSplit (float bestGainRatio, int bestDim, float bestVal, int bestType)
void	initStump ()
void	outputProbabilities (std::multiset< float > outputs, std::map< float, float > *retval)
bool	passTest (int dim, float val, int type, const std::vector< float > &input)
void	printStump ()
void	setParams (float margin, float forestPct, float minRatio)
float *	sortOnDim (int dim)
	Stump (int id, int trainMode, int trainFreq, int m, float featPct, Random rng)
	Stump (const Stump &)
void	testInstance (const std::vector< float > &input, std::map< float, float > *retval)
void	testPossibleSplits (float *bestGainRatio, int *bestDim, float *bestVal, int *bestType)
bool	trainInstance (classPair &instance)
bool	trainInstances (std::vector< classPair > &instances)
	~Stump ()
Public Attributes
bool	ALLOW_ONLY_SPLITS
float	LOSS_MARGIN
float	MIN_GAIN_RATIO
int	nExperiences
float	REBUILD_RATIO
float	SPLIT_MARGIN
bool	SPLITDEBUG
bool	STDEBUG
Private Attributes
stump_experience	allExp [N_STUMP_EXP]
int	dim
std::vector< stump_experience * >	experiences
float	featPct
const int	freq
float	gainRatio
const int	id
std::multiset< float >	leftOutputs
const int	M
const int	mode
int	nnodes
int	nOutput
std::multiset< float >	rightOutputs
Random	rng
int	type
float	val

---

Detailed Description

C4.5 decision stump class

Definition at line 13 of file Stump.hh.

---

Member Enumeration Documentation

enum Stump::splitTypes

Enumerator:

ONLY
CUT

Definition at line 35 of file Stump.hh.

---

Constructor & Destructor Documentation

Stump::Stump	(	int	id,
		int	trainMode,
		int	trainFreq,
		int	m,
		float	featPct,
		Random	rng
	)

Definition at line 5 of file Stump.cc.

Stump::Stump

(

const Stump &

s

)

Definition at line 35 of file Stump.cc.

Stump::~Stump

(

)

Definition at line 72 of file Stump.cc.

---

Member Function Documentation

void Stump::buildStump

(

)

Build the stump from this node down using this set of experiences.

Definition at line 366 of file Stump.cc.

float Stump::calcGainRatio	(	int	dim,
		float	val,
		int	type,
		float	I
	)

Calculate gain ratio for this possible split.

Definition at line 550 of file Stump.cc.

float Stump::calcIforSet

(

const std::vector< stump_experience * > &

instances

)

Calculate I(P) for set.

Definition at line 627 of file Stump.cc.

float Stump::calcIofP	(	float *	P,
		int	size
	)

Definition at line 617 of file Stump.cc.

void Stump::compareSplits	(	float	gainRatio,
		int	dim,
		float	val,
		int	type,
		int *	nties,
		float *	bestGainRatio,
		int *	bestDim,
		float *	bestVal,
		int *	bestType
	)

Decide if this split is better.

Definition at line 500 of file Stump.cc.

int Stump::findMatching	(	const std::vector< stump_experience * > &	instances,
		int	dim,
		int	val,
		int	minConf
	)

Definition at line 302 of file Stump.cc.

float Stump::getConf

(

const std::vector< float > &

input

)

[virtual]

Implements Classifier.

Definition at line 284 of file Stump.cc.

Stump * Stump::getCopy

(

)

[virtual]

Implements Classifier.

Definition at line 67 of file Stump.cc.

void Stump::implementSplit	(	float	bestGainRatio,
		int	bestDim,
		float	bestVal,
		int	bestType
	)

Definition at line 390 of file Stump.cc.

void Stump::initStump

(

)

Definition at line 322 of file Stump.cc.

void Stump::outputProbabilities	(	std::multiset< float >	outputs,
		std::map< float, float > *	retval
	)

See if the attributes are independent of the output class If they are all independent, we have no more inputs to split on

Definition at line 855 of file Stump.cc.

bool Stump::passTest	(	int	dim,
		float	val,
		int	type,
		const std::vector< float > &	input
	)

Decide if this passes the test

Definition at line 342 of file Stump.cc.

void Stump::printStump

(

)

Print the stump for debug purposes.

Definition at line 728 of file Stump.cc.

void Stump::setParams	(	float	margin,
		float	forestPct,
		float	minRatio
	)

float * Stump::sortOnDim

(

int

dim

)

Returns a list of the attributes in this dimension sorted from lowest to highest.

Definition at line 672 of file Stump.cc.

void Stump::testInstance	(	const std::vector< float > &	input,
		std::map< float, float > *	retval
	)		[virtual]

Implements Classifier.

Definition at line 265 of file Stump.cc.

void Stump::testPossibleSplits	(	float *	bestGainRatio,
		int *	bestDim,
		float *	bestVal,
		int *	bestType
	)

Definition at line 433 of file Stump.cc.

bool Stump::trainInstance

(

classPair &

instance

)

[virtual]

Implements Classifier.

Definition at line 173 of file Stump.cc.

bool Stump::trainInstances

(

std::vector< classPair > &

instances

)

[virtual]

Implements Classifier.

Definition at line 81 of file Stump.cc.

---

Member Data Documentation

stump_experience Stump::allExp[N_STUMP_EXP] [private]

Definition at line 96 of file Stump.hh.

bool Stump::ALLOW_ONLY_SPLITS

Definition at line 69 of file Stump.hh.

int Stump::dim [private]

Definition at line 99 of file Stump.hh.

std::vector<stump_experience*> Stump::experiences [private]

Definition at line 95 of file Stump.hh.

float Stump::featPct [private]

Definition at line 87 of file Stump.hh.

const int Stump::freq [private]

Definition at line 85 of file Stump.hh.

float Stump::gainRatio [private]

Definition at line 102 of file Stump.hh.

const int Stump::id [private]

Definition at line 82 of file Stump.hh.

std::multiset<float> Stump::leftOutputs [private]

Definition at line 105 of file Stump.hh.

float Stump::LOSS_MARGIN

Definition at line 78 of file Stump.hh.

const int Stump::M [private]

Definition at line 86 of file Stump.hh.

float Stump::MIN_GAIN_RATIO

Definition at line 76 of file Stump.hh.

const int Stump::mode [private]

Definition at line 84 of file Stump.hh.

int Stump::nExperiences

Definition at line 73 of file Stump.hh.

int Stump::nnodes [private]

Definition at line 92 of file Stump.hh.

int Stump::nOutput [private]

Definition at line 91 of file Stump.hh.

float Stump::REBUILD_RATIO

Definition at line 77 of file Stump.hh.

std::multiset<float> Stump::rightOutputs [private]

Definition at line 106 of file Stump.hh.

Random Stump::rng [private]

Definition at line 89 of file Stump.hh.

float Stump::SPLIT_MARGIN

Definition at line 75 of file Stump.hh.

bool Stump::SPLITDEBUG

Definition at line 72 of file Stump.hh.

bool Stump::STDEBUG

Definition at line 71 of file Stump.hh.

int Stump::type [private]

Definition at line 101 of file Stump.hh.

float Stump::val [private]

Definition at line 100 of file Stump.hh.

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The documentation for this class was generated from the following files:

• Stump.hh
• Stump.cc