latest version v1.9 - last update 24 Nov 2005

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.

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)
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...

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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.

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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

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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

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

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.

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

• ltiCrispDecisionTree.h

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