RapidLib  v0.1.2
A simple library for interactive machine learning
knnClassification Class Reference

#include <knnClassification.h>

Inheritance diagram for knnClassification:
Inheritance graph
Collaboration diagram for knnClassification:
Collaboration graph

Public Member Functions

 knnClassification (const int &num_inputs, const std::vector< int > &which_inputs, const std::vector< trainingExample > &trainingSet, const int &k)
 
 ~knnClassification ()
 
void addNeighbour (const int &classNum, const std::vector< double > &features)
 
double process (const std::vector< double > &inputVector)
 
void train (const std::vector< trainingExample > &trainingSet)
 
int getNumInputs ()
 
std::vector< int > getWhichInputs ()
 
void getJSONDescription (Json::Value &currentModel)
 
- Public Member Functions inherited from baseModel
virtual ~baseModel ()
 

Additional Inherited Members

- Protected Member Functions inherited from baseModel
template<typename T >
Json::Value vector2json (T vec)
 

Detailed Description

Class for implementing a knn classifier

Constructor & Destructor Documentation

§ knnClassification()

knnClassification::knnClassification ( const int &  num_inputs,
const std::vector< int > &  which_inputs,
const std::vector< trainingExample > &  trainingSet,
const int &  k 
)

Constructor that takes training examples in

Parameters
numberof inputs expected in the training and input vectors
vectorof input numbers to be fed into the classifer.
vectorof training examples
howmany near neighbours to evaluate

§ ~knnClassification()

knnClassification::~knnClassification ( )

Member Function Documentation

§ addNeighbour()

void knnClassification::addNeighbour ( const int &  classNum,
const std::vector< double > &  features 
)

add another example to the existing training set

Parameters
classnumber of example
featurevector of example

§ getJSONDescription()

void knnClassification::getJSONDescription ( Json::Value &  currentModel)
virtual

Implements baseModel.

§ getNumInputs()

int knnClassification::getNumInputs ( )
virtual

Implements baseModel.

§ getWhichInputs()

std::vector< int > knnClassification::getWhichInputs ( )
virtual

Implements baseModel.

§ process()

double knnClassification::process ( const std::vector< double > &  inputVector)
virtual

Generate an output value from a single input vector.

Parameters
Astandard vector of doubles to be evaluated.
Returns
A single double: the nearest class as determined by k-nearest neighbor.

Implements baseModel.

§ train()

void knnClassification::train ( const std::vector< trainingExample > &  trainingSet)
virtual

Fill the model with a vector of examples.

Parameters
Thetraining set is a vector of training examples that contain both a vector of input values and a double specifying desired output class.

Implements baseModel.


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