gpmp::ml::KohonenNet Class Reference

Kohonen Neural Network Cluster Class. More...

#include <kohonen_net.hpp>

Public Member Functions
	KohonenNet (int inputSize, int mapSize)
	Constructor for the KohonenNet class. More...
	~KohonenNet ()
	Destructor for the KohonenNet class. More...
void	train (const std::vector< std::vector< double >> &inputData, int epochs=1000)
	Trains the Kohonen network using input data. More...
int	classify (const std::vector< double > &inputVector)
	Classifies a given input vector and returns the index of the best matching unit. More...

Private Member Functions
void	initialize_weights ()
	Initializes the weights of the Kohonen network. More...
int	best_matching_unit (const std::vector< double > &input_vector)
	Finds the index of the best matching unit (BMU) for a given input vector. More...
void	update_weights (int bmu, const std::vector< double > &input_vector, double learning_rate)
	Updates the weights of the Kohonen network based on the best matching unit and input vector. More...
double	euclidean_distance (const std::vector< double > &vec1, const std::vector< double > &vec2)
	Calculates the Euclidean distance between two vectors. More...

Private Attributes
int	input_size
int	map_size
std::vector< std::vector< double > >	weights

Detailed Description

Kohonen Neural Network Cluster Class.

Referred to as Self-Organizing Map

Definition at line 52 of file kohonen_net.hpp.

Constructor & Destructor Documentation

KohonenNet()

gpmp::ml::KohonenNet::KohonenNet	(	int	inputSize,
		int	mapSize
	)

Constructor for the KohonenNet class.

Parameters

inputSize	The size of the input vector
mapSize	The size of the map in the Kohonen network

Definition at line 38 of file kohonen_net.cpp.

    : input_size(in_size), map_size(m_size) {
    initialize_weights();
}

References initialize_weights().

~KohonenNet()

gpmp::ml::KohonenNet::~KohonenNet

(

)

Destructor for the KohonenNet class.

Definition at line 43 of file kohonen_net.cpp.

                              {
}

Member Function Documentation

best_matching_unit()

int gpmp::ml::KohonenNet::best_matching_unit ( const std::vector< double > &  input_vector )

private

Finds the index of the best matching unit (BMU) for a given input vector.

Parameters

input_vector

The input vector

Returns

The index of the best matching unit

Definition at line 74 of file kohonen_net.cpp.

                                          {
    int bmu = 0;
    double minDistance = euclidean_distance(inputVector, weights[0]);
 
    for (int i = 1; i < map_size; ++i) {
        double distance = euclidean_distance(inputVector, weights[i]);
        if (distance < minDistance) {
            minDistance = distance;
            bmu = i;
        }
    }
 
    return bmu;
}

classify()

int gpmp::ml::KohonenNet::classify

(

const std::vector< double > &

inputVector

)

Classifies a given input vector and returns the index of the best matching unit.

Parameters

inputVector

The input vector to be classified

Returns

The index of the best matching unit

Definition at line 70 of file kohonen_net.cpp.

                                                                   {
    return best_matching_unit(inputVector);
}

euclidean_distance()

double gpmp::ml::KohonenNet::euclidean_distance ( const std::vector< double > &  vec1, const std::vector< double > &  vec2  )

private

Calculates the Euclidean distance between two vectors.

Parameters

vec1	The first vector
vec2	The second vector

Returns

The Euclidean distance between the two vectors

Definition at line 101 of file kohonen_net.cpp.

                                                                        {
    double distance = 0.0;
    for (size_t i = 0; i < vec1.size(); ++i) {
        double diff = vec1[i] - vec2[i];
        distance += diff * diff;
    }
    return sqrt(distance);
}

initialize_weights()

void gpmp::ml::KohonenNet::initialize_weights ( )

private

Initializes the weights of the Kohonen network.

Definition at line 46 of file kohonen_net.cpp.

                                          {
    weights.resize(map_size, std::vector<double>(input_size));
 
    // Initialize weights randomly or using some other strategy
    // For simplicity, we initialize them with random values between 0 and 1
    for (int i = 0; i < map_size; ++i) {
        for (int j = 0; j < input_size; ++j) {
            weights[i][j] = static_cast<double>(rand()) / RAND_MAX;
        }
    }
}

Referenced by KohonenNet().

train()

void gpmp::ml::KohonenNet::train	(	const std::vector< std::vector< double >> &	inputData,
		int	epochs = 1000
	)

Trains the Kohonen network using input data.

Parameters

inputData	The input data consisting of vectors
epochs	The number of training epochs (default: 1000)

Definition at line 58 of file kohonen_net.cpp.

                {
    for (int epoch = 0; epoch < epochs; ++epoch) {
        for (const auto &inputVector : inputData) {
            int bmu = best_matching_unit(inputVector);
            double learningRate = 1.0 - static_cast<double>(epoch) / epochs;
            update_weights(bmu, inputVector, learningRate);
        }
    }
}

update_weights()

void gpmp::ml::KohonenNet::update_weights ( int  bmu, const std::vector< double > &  input_vector, double  learning_rate  )

private

Updates the weights of the Kohonen network based on the best matching unit and input vector.

Parameters

bmu	The index of the best matching unit
input_vector	The input vector
learning_rate	The learning rate for weight updates

Definition at line 90 of file kohonen_net.cpp.

                         {
    for (int i = 0; i < input_size; ++i) {
        double delta = inputVector[i] - weights[bmu][i];
        weights[bmu][i] += learningRate * delta;
    }
}

Member Data Documentation

input_size

int gpmp::ml::KohonenNet::input_size

private

The size of the input vector

Definition at line 82 of file kohonen_net.hpp.

map_size

int gpmp::ml::KohonenNet::map_size

private

The size of the map in the Kohonen network

Definition at line 83 of file kohonen_net.hpp.

weights

std::vector<std::vector<double> > gpmp::ml::KohonenNet::weights

private

Weight matrix for the Kohonen network

Definition at line 85 of file kohonen_net.hpp.

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

• include/openGPMP/ml/kohonen_net.hpp
• modules/ml/kohonen_net.cpp