The mean squared error performance function measures the network's performance according to the mean of squared errors.
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#include <mean_squared_error.hpp>
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| MeanSquaredError () |
| | Create the MeanSquaredError object.
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| template<typename PredictionType , typename TargetType > |
| PredictionType::elem_type | Forward (const PredictionType &prediction, const TargetType &target) |
| | Computes the mean squared error function. More...
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| template<typename PredictionType , typename TargetType , typename LossType > |
| void | Backward (const PredictionType &prediction, const TargetType &target, LossType &loss) |
| | Ordinary feed backward pass of a neural network. More...
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OutputDataType & | OutputParameter () const |
| | Get the output parameter.
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OutputDataType & | OutputParameter () |
| | Modify the output parameter.
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template<typename Archive > |
| void | serialize (Archive &ar, const uint32_t) |
| | Serialize the layer.
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template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat>
class mlpack::ann::MeanSquaredError< InputDataType, OutputDataType >
The mean squared error performance function measures the network's performance according to the mean of squared errors.
- Template Parameters
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| ActivationFunction | Activation function used for the embedding layer. |
| InputDataType | Type of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube). |
| OutputDataType | Type of the output data (arma::colvec, arma::mat, arma::sp_mat or arma::cube). |
◆ Backward()
template<typename InputDataType , typename OutputDataType >
template<typename PredictionType , typename TargetType , typename LossType >
| void mlpack::ann::MeanSquaredError< InputDataType, OutputDataType >::Backward |
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const PredictionType & |
prediction, |
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const TargetType & |
target, |
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LossType & |
loss |
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Ordinary feed backward pass of a neural network.
- Parameters
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| prediction | Predictions used for evaluating the specified loss function |
| target | The target vector. |
| loss | The calculated error. |
◆ Forward()
template<typename InputDataType , typename OutputDataType >
template<typename PredictionType , typename TargetType >
| PredictionType::elem_type mlpack::ann::MeanSquaredError< InputDataType, OutputDataType >::Forward |
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const PredictionType & |
prediction, |
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const TargetType & |
target |
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Computes the mean squared error function.
- Parameters
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| prediction | Predictions used for evaluating the specified loss function. |
| target | The target vector. |
The documentation for this class was generated from the following files:
