#include <shark/ObjectiveFunctions/Loss/SquaredLoss.h>
Public Member Functions | |
SquaredLoss (std::size_t ignore=0) | |
Constructor. More... | |
std::string | name () const |
From INameable: return the class name. More... | |
double | eval (BatchLabelType const &labels, BatchOutputType const &predictions) const |
Evaluate the squared loss \( (label - prediction)^2 \). More... | |
double | evalDerivative (BatchLabelType const &labels, BatchOutputType const &predictions, BatchOutputType &gradient) const |
Public Member Functions inherited from shark::AbstractLoss< Sequence, Sequence > | |
AbstractLoss () | |
virtual double | eval (ConstLabelReference target, ConstOutputReference prediction) const |
evaluate the loss for a target and a prediction More... | |
double | eval (Data< LabelType > const &targets, Data< OutputType > const &predictions) const |
virtual double | evalDerivative (ConstLabelReference target, ConstOutputReference prediction, OutputType &gradient) const |
evaluate the loss and its derivative for a target and a prediction More... | |
virtual double | evalDerivative (ConstLabelReference target, ConstOutputReference prediction, OutputType &gradient, MatrixType &hessian) const |
evaluate the loss and its first and second derivative for a target and a prediction More... | |
double | operator() (LabelType const &target, OutputType const &prediction) const |
evaluate the loss for a target and a prediction More... | |
double | operator() (BatchLabelType const &target, BatchOutputType const &prediction) const |
Public Member Functions inherited from shark::AbstractCost< Sequence, Sequence > | |
virtual | ~AbstractCost () |
const Features & | features () const |
virtual void | updateFeatures () |
bool | hasFirstDerivative () const |
returns true when the first parameter derivative is implemented More... | |
bool | isLossFunction () const |
returns true when the cost function is in fact a loss function More... | |
double | operator() (Data< LabelType > const &targets, Data< OutputType > const &predictions) const |
Public Member Functions inherited from shark::INameable | |
virtual | ~INameable () |
Definition at line 140 of file SquaredLoss.h.
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inline |
Constructor.
ignore | Specifies how many elements of the sequence are to be ignored during evaluation must be strictly smaller than the smalles sequnce to evaluate. |
Definition at line 147 of file SquaredLoss.h.
References shark::AbstractCost< LabelType, OutputType >::HAS_FIRST_DERIVATIVE, and shark::AbstractCost< LabelType, OutputType >::m_features.
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inlinevirtual |
Evaluate the squared loss \( (label - prediction)^2 \).
For Sequences this is:
\[ sum_{i=i_0} (label_i-prediction_i)^2\]
where \( i_0 \) is the first element to be evaluated. By default it is 0
Implements shark::AbstractLoss< Sequence, Sequence >.
Definition at line 164 of file SquaredLoss.h.
References SHARK_RUNTIME_CHECK, and SIZE_CHECK.
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inlinevirtual |
Evaluate the squared loss \( (label - prediction)^2 \) and its deriative \( \frac{\partial}{\partial prediction} 1/2 (label - prediction)^2 = prediction - label \).
Reimplemented from shark::AbstractLoss< Sequence, Sequence >.
Definition at line 181 of file SquaredLoss.h.
References SHARK_RUNTIME_CHECK, and SIZE_CHECK.
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inlinevirtual |
From INameable: return the class name.
Reimplemented from shark::INameable.
Definition at line 154 of file SquaredLoss.h.
References shark::AbstractLoss< LabelType, OutputType >::eval().