~sgould/darwin/classdrwnFisherLDA.html

// load training dataset

drwnClassifierDataset dataset;

dataset.read("training.bin");


// compute LDA features

drwnFisherLDA lda;

lda.train(dataset.features, dataset.labels);

lda.transform(dataset.features);


// save LDA features

dataset.write("training_lda.bin");


// apply same transformation to test dataset

dataset.clear();

dataset.read("testing.bin");

lda.transform(dataset.features);

dataset.write("testing_lda.bin");
Public Member Functions
	drwnFisherLDA ()
	default constructor

	drwnFisherLDA (const drwnFisherLDA &lda)
	copy constructor

const char *	type () const
	returns object type as a string (e.g., Foo::type() { return "Foo"; })

drwnFisherLDA *	clone () const
	returns a copy of the class usually implemented as virtual Foo* clone() { return new Foo(*this); }

void	clear ()
	clears the parameters of the feature transform object

bool	save (drwnXMLNode &node) const
	write object to XML node (see also write)

bool	load (drwnXMLNode &node)
	read object from XML node (see also read)

int	numInputs () const
	feature vector size for the input space

int	numOutputs () const
	feature vector size for the output space

double	train (const drwnCondSuffStats &stats)
	Estimate the parameters of the feature transformation from previously accumulated second-order conditional sufficient statistics.

double	train (const vector< vector< double > > &features, const vector< int > &labels)
	Estimate the parameters of the features transformation. This function must be implemented in the derived class.

double	train (const vector< vector< double > > &features, const vector< int > &labels, const vector< double > &weights)
	Estimate the parameters of the feature transformation using weighted training examples.

double	train (const vector< vector< double > > &features, const vector< int > &labels, const drwnFeatureTransform &xform)
	Estimate the parameters of the features transformation first applying another transform. The default implementation of this function naively transforms the data and passes the transformed data onto the relevant training code.

double	train (const vector< vector< double > > &features, const vector< int > &labels, const vector< double > &weights, const drwnFeatureTransform &xform)
	Estimate the parameters of the feature transformation using weighted training examples first applying another transform. The default implementation of this function naively transforms the data and passes the transformed data onto the relevant training code.

void	transform (const vector< double > &x, vector< double > &y) const
	transforms feature vector `x` into feature vector `y`

Public Member Functions inherited from drwnSupervisedTransform
	drwnSupervisedTransform ()
	default constructor

	drwnSupervisedTransform (const drwnSupervisedTransform &t)
	copy constructor

Public Member Functions inherited from drwnFeatureTransform
	drwnFeatureTransform ()
	default constructor

	drwnFeatureTransform (const drwnFeatureTransform &t)
	copy constructor

int	numFeatures () const
	returns the length of the feature vector expected by the feature transform object (or zero for arbitrary)

virtual bool	valid () const
	returns true if the feature transform object is initialized (and trained)

virtual void	transform (vector< double > &x) const
	transforms a feature vector in-place

virtual void	transform (vector< vector< double > > &x) const
	transforms a set of feature vectors in-place

virtual void	transform (const vector< vector< double > > &x, vector< vector< double > > &y) const
	transforms a set of feature vectors from `x` to corresponding feature vectors `y`

virtual void	transform (vector< double > &x, const drwnFeatureTransform &xform) const
	transforms a feature vector in-place first applying another transform

virtual void	transform (const vector< double > &x, vector< double > &y, const drwnFeatureTransform &xform) const
	transforms feature vector `x` into feature vector `y` first applying another transform

virtual void	transform (vector< vector< double > > &x, const drwnFeatureTransform &xform) const
	transforms a set of feature vectors in-place first applying another transform

virtual void	transform (const vector< vector< double > > &x, vector< vector< double > > &y, const drwnFeatureTransform &xform) const
	transforms a set of feature vectors from `x` to corresponding feature vectors `y` first applying another transform

Public Member Functions inherited from drwnWriteable
bool	write (const char *filename) const
	write object to file (calls save)

bool	read (const char *filename)
	read object from file (calls load)

void	dump () const
	print object's current state to standard output (for debugging)

Public Member Functions inherited from drwnProperties
unsigned	numProperties () const

bool	hasProperty (const string &name) const

bool	hasProperty (const char *name) const

unsigned	findProperty (const string &name) const

unsigned	findProperty (const char *name) const

void	setProperty (unsigned indx, bool value)

void	setProperty (unsigned indx, int value)

void	setProperty (unsigned indx, double value)

void	setProperty (unsigned indx, const string &value)

void	setProperty (unsigned indx, const char *value)

void	setProperty (unsigned indx, const Eigen::VectorXd &value)

void	setProperty (unsigned indx, const Eigen::MatrixXd &value)

void	setProperty (const char *name, bool value)

void	setProperty (const char *name, int value)

void	setProperty (const char *name, double value)

void	setProperty (const char *name, const string &value)

void	setProperty (const char name, const char value)

void	setProperty (const char *name, const Eigen::VectorXd &value)

void	setProperty (const char *name, const Eigen::MatrixXd &value)

string	getPropertyAsString (unsigned indx) const

drwnPropertyType	getPropertyType (unsigned indx) const

bool	isReadOnly (unsigned indx) const

const drwnPropertyInterface *	getProperty (unsigned indx) const

const drwnPropertyInterface *	getProperty (const char *name) const

bool	getBoolProperty (unsigned indx) const

int	getIntProperty (unsigned indx) const

double	getDoubleProperty (unsigned indx) const

const string &	getStringProperty (unsigned indx) const

const list< string > &	getListProperty (unsigned indx) const

int	getSelectionProperty (unsigned indx) const

const Eigen::VectorXd &	getVectorProperty (unsigned indx) const

const Eigen::MatrixXd &	getMatrixProperty (unsigned indx) const

const string &	getPropertyName (unsigned indx) const

vector< string >	getPropertyNames () const

void	readProperties (drwnXMLNode &xml, const char *tag="property")

void	writeProperties (drwnXMLNode &xml, const char *tag="property") const

void	printProperties (ostream &os) const
Additional Inherited Members
Protected Member Functions inherited from drwnProperties
void	declareProperty (const string &name, drwnPropertyInterface *optif)

void	undeclareProperty (const string &name)

void	exposeProperties (drwnProperties *opts, const string &prefix=string(""), bool bSerializable=false)

virtual void	propertyChanged (const string &name)

Protected Attributes inherited from drwnFeatureTransform
int	_nFeatures
	number of (input) features

bool	_bValid
	true if transform parameters are trained or loaded