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drwnClassifier Class Referenceabstract

Implements the interface for a generic machine learning classifier. More...

Inheritance diagram for drwnClassifier:
drwnStdObjIface drwnProperties drwnWriteable drwnCloneable drwnTypeable drwnBoostedClassifier drwnCompositeClassifier drwnDecisionTree drwnMultiClassLogisticBase drwnRandomForest drwnTMultiClassLogistic< FeatureMap > drwnTMultiClassLogistic< drwnBiasJointFeatureMap >

Public Member Functions

 drwnClassifier ()
 default constructor
 
 drwnClassifier (unsigned n, unsigned k=2)
 construct a classifer with n features and k classes
 
 drwnClassifier (const drwnClassifier &c)
 copy constructor
 
int numFeatures () const
 returns the number of features expected by the classifier object
 
int numClasses () const
 returns the number of classes predicted by the classifier object
 
virtual bool valid () const
 returns true if the classifier is valid (has been initialized and trained)
 
virtual void initialize (unsigned n, unsigned k=2)
 initialize the classifier object for n features and k classes
 
virtual drwnClassifierclone () const =0
 returns a copy of the class usually implemented as virtual Foo* clone() { return new Foo(*this); }
 
virtual bool save (drwnXMLNode &xml) const
 write object to XML node (see also write)
 
virtual bool load (drwnXMLNode &xml)
 read object from XML node (see also read)
 
virtual double train (const drwnClassifierDataset &dataset)=0
 train the parameters of the classifier from a drwnClassifierDataset object
 
virtual double train (const vector< vector< double > > &features, const vector< int > &targets)
 train the parameters of the classifier from a set of features and corresponding labels
 
virtual double train (const vector< vector< double > > &features, const vector< int > &targets, const vector< double > &weights)
 train the parameters of the classifier from a weighted set of features and corresponding labels
 
virtual double train (const char *filename)
 train the parameters of the classifier from data stored in filename
 
virtual void getClassScores (const vector< double > &features, vector< double > &outputScores) const =0
 compute the unnormalized log-probability for a single feature vector
 
virtual void getClassScores (const vector< vector< double > > &features, vector< vector< double > > &outputScores) const
 compute the unnormalized log-probability for a set of feature vectors
 
virtual void getClassMarginals (const vector< double > &features, vector< double > &outputMarginals) const
 compute the class marginal probabilities for a single feature vector
 
virtual void getClassMarginals (const vector< vector< double > > &features, vector< vector< double > > &outputMarginals) const
 compute the class marginal probabilities for a set of feature vectors
 
virtual int getClassification (const vector< double > &features) const
 return the most likely class label for a single feature vector
 
virtual void getClassifications (const vector< vector< double > > &features, vector< int > &outputLabels) const
 compute the most likely class labels for a set of feature vector
 
- 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 drwnTypeable
virtual const char * type () const =0
 returns object type as a string (e.g., Foo::type() { return "Foo"; })
 
- 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 drwnPropertyInterfacegetProperty (unsigned indx) const
 
const drwnPropertyInterfacegetProperty (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
 

Protected Attributes

int _nFeatures
 number of features
 
int _nClasses
 number of classes
 
bool _bValid
 true if the classifier has been trained or loaded
 

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)
 

Detailed Description

Implements the interface for a generic machine learning classifier.

Derived classes must implement training and evaluation methods and should also override XML save and load methods, and optionally the initialize method.

See Also
drwnML Tutorial

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