NeuralNet::Loss Class Reference

Inheritance diagram for NeuralNet::Loss:

Static Public Member Functions
static double	cmpLoss (const Eigen::MatrixXd &o, const Eigen::MatrixXd &y)
	This function computes the loss of the current iteration.
static Eigen::MatrixXd	cmpLossGrad (const Eigen::MatrixXd &yHat, const Eigen::MatrixXd &y)
	This function computes the loss gradient w.r.t the outputs.

Member Function Documentation

cmpLoss()

static double NeuralNet::Loss::cmpLoss ( const Eigen::MatrixXd & o, const Eigen::MatrixXd & y )

static

This function computes the loss of the current iteration.

Parameters

o	The outputs from the output layer
y	The labels (the expected values)

Returns

The loss based on the selected loss function

cmpLossGrad()

static Eigen::MatrixXd NeuralNet::Loss::cmpLossGrad ( const Eigen::MatrixXd & yHat, const Eigen::MatrixXd & y )

static

This function computes the loss gradient w.r.t the outputs.

Parameters

yHat	The outputs from the output layer
y	The labels (expected vals)

Returns

The current iteration's gradient

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

• /github/workspace/src/NeuralNet/losses/Loss.hpp