lti::crispDecisionTree Class Reference

Base class for all crisp decision trees. More...

#include <ltiCrispDecisionTree.h>

Inheritance diagram for lti::crispDecisionTree:

[legend]

Collaboration diagram for lti::crispDecisionTree:

[legend]

List of all members.

Classes
class	crispDecisionFunction
	Base class for decision functions of crispNode. More...
class	crispNode
	A crisp decision tree node. More...
class	multivariateCrispDecisionFunction
	This class implements a multivariate decision. More...
class	parameters
	the parameters for the class crispDecisionTree More...
class	univariateCrispDecisionFunction
	This class implements the most common decision function: Each node has a real-valued threshold in one dimension only. More...
Public Member Functions
	crispDecisionTree ()
	crispDecisionTree (const crispDecisionTree &other)
virtual	~crispDecisionTree ()
virtual const char *	getTypeName () const
crispDecisionTree &	copy (const crispDecisionTree &other)
crispDecisionTree &	operator= (const crispDecisionTree &other)
const parameters &	getParameters () const
virtual bool	classify (const dvector &feature, outputVector &result) const
virtual bool	write (ioHandler &handler, const bool complete=true) const
virtual bool	read (ioHandler &handler, const bool complete=true)

---

Detailed Description

Base class for all crisp decision trees.

A crisp decision tree has the following properties:

• Each node has zero, one or two children.
• Propagation of a vector results in one (or zero) leaf nodes being activated
• The exact type of the node as well as the condition in the decision function can be chosen for each node individually.

---

Constructor & Destructor Documentation

lti::crispDecisionTree::crispDecisionTree

(

)

default constructor

lti::crispDecisionTree::crispDecisionTree

(

const crispDecisionTree &

other

)

copy constructor

Parameters:

other

the object to be copied

virtual lti::crispDecisionTree::~crispDecisionTree

(

)

[virtual]

destructor

---

Member Function Documentation

virtual bool lti::crispDecisionTree::classify	(	const dvector &	feature,
		outputVector &	result
	)			const [virtual]

Classification.

Classifies the feature and returns the outputVector with the classification result.

Parameters:

	feature	the vector to be classified
	result	the result of the classification

Returns:

false if an error occurred during classification else true

Implements lti::supervisedInstanceClassifier.

crispDecisionTree& lti::crispDecisionTree::copy

(

const crispDecisionTree &

other

)

copy data of "other" classifier.

Parameters:

other

the classifier to be copied

Returns:

a reference to this functor object

Reimplemented from lti::decisionTree.

Reimplemented in lti::manualCrispDecisionTree.

const parameters& lti::crispDecisionTree::getParameters

(

)

const

returns used parameters

Reimplemented from lti::decisionTree.

Reimplemented in lti::manualCrispDecisionTree.

virtual const char* lti::crispDecisionTree::getTypeName

(

)

const [virtual]

returns the name of this type ("crispDecisionTree")

Reimplemented from lti::decisionTree.

Reimplemented in lti::manualCrispDecisionTree.

crispDecisionTree& lti::crispDecisionTree::operator=

(

const crispDecisionTree &

other

)

alias for copy member

Parameters:

other

the classifier to be copied

Returns:

a reference to this classifier object

Reimplemented from lti::decisionTree.

Reimplemented in lti::manualCrispDecisionTree.

virtual bool lti::crispDecisionTree::read	(	ioHandler &	handler,
		const bool	complete = true
	)			[virtual]

read the parameters from the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:

true if write was successful

Reimplemented from lti::decisionTree.

virtual bool lti::crispDecisionTree::write	(	ioHandler &	handler,
		const bool	complete = true
	)			const [virtual]

write the parameters in the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:

true if write was successful

Reimplemented from lti::decisionTree.

---

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

• ltiCrispDecisionTree.h