netdem::MLPackUtils Class Reference

A class that defines several utility methods for ANN. More...

#include <mlpack_utils.hpp>

Public Types
enum class	LayerType {   Identity , Linear , ReLU , LeakyReLU ,   ELU , Softmax , LogSoftMax }
	An enumeration of neural network layer types. More...

Static Public Member Functions
static double	GetMSE (const arma::mat &pred, const arma::mat &Y)
	Calculates the mean squared error between predicted and ground truth data.
static double	GetMAE (const arma::mat &pred, const arma::mat &Y)
	Calculates the mean absolute error between predicted and ground truth data.
static arma::mat	GetLabels (const arma::mat &ann_outputs)
	Converts continuous output vectors to class labels.

Detailed Description

A class that defines several utility methods for ANN.

Member Enumeration Documentation

LayerType

enum class netdem::MLPackUtils::LayerType

strong

An enumeration of neural network layer types.

The LayerType enumeration represents different types of neural network layers. It is used to specify which type of layer to add to a neural network model.

Enumerator
Identity	The identity layer type.
Linear	The linear layer type.
ReLU	The rectified linear unit (ReLU) layer type.
LeakyReLU	The leaky ReLU layer type.
ELU	The exponential linear unit (ELU) layer type.
Softmax	The softmax layer type.
LogSoftMax	The log-softmax layer type.

Member Function Documentation

GetLabels()

arma::mat netdem::MLPackUtils::GetLabels ( const arma::mat & ann_outputs )

static

Converts continuous output vectors to class labels.

This function converts continuous output vectors to class labels by selecting the index of the maximum value in each row.

Parameters

ann_outputs

The output data matrix.

Returns

The predicted class labels as a matrix of size (1 x num_samples).

GetMAE()

double netdem::MLPackUtils::GetMAE ( const arma::mat & pred, const arma::mat & Y )

static

Calculates the mean absolute error between predicted and ground truth data.

This function calculates the mean absolute error (MAE) between two matrices of predicted and ground truth data.

Parameters

pred	The predicted data matrix.
Y	The ground truth data matrix.

Returns

The calculated MAE as a scalar value.

GetMSE()

double netdem::MLPackUtils::GetMSE ( const arma::mat & pred, const arma::mat & Y )

static

Calculates the mean squared error between predicted and ground truth data.

This function calculates the mean squared error (MSE) between two matrices of predicted and ground truth data.

Parameters

pred	The predicted data matrix.
Y	The ground truth data matrix.

Returns

The calculated MSE as a scalar value.

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

• /Users/lzhshou/Documents/Research/myProjects/apaam/repo/netdem/src/mlpack/mlpack_utils.hpp
• /Users/lzhshou/Documents/Research/myProjects/apaam/repo/netdem/src/mlpack/mlpack_utils.cpp