Class LinearModelMSE¶
Defined in File model.h
Inheritance Relationships¶
Base Type¶
public parpe::SummedGradientFunction< int >
(Template Class SummedGradientFunction)
Class Documentation¶
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class LinearModelMSE : public parpe::SummedGradientFunction<int>¶
The LinearModelMSE class is a wrapper around LinearModel implementing the mean squared error loss function.
Public Functions
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inline explicit LinearModelMSE(int numParameters)¶
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inline virtual FunctionEvaluationStatus evaluate(gsl::span<const double> parameters, int dataset, double &fval, gsl::span<double> gradient, Logger *logger, double *cpuTime) const override¶
Evaluate on single data point.
- Parameters:
parameters – Parameter vector where the function is to be evaluated
dataset – The dataset on which to evaluate the function
fval – Output argument for f(x)
gradient – Preallocated space for the gradient of size dim(parameters). Or gsl::span<double>() for evaluation without gradient.
logger – Optional Logger instance used for output
cputime – Optional output argument to report cpuTime consumed by the the function
- Returns:
Evaluation status
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virtual FunctionEvaluationStatus evaluate(gsl::span<const double> parameters, std::vector<int> dataIndices, double &fval, gsl::span<double> gradient, Logger *logger, double *cpuTime) const override¶
Evaluate on vector of data points.
- Parameters:
parameters – Parameter vector where the function is to be evaluated
datasets – The datasets on which to evaluate the function
fval – Output argument for f(x)
gradient – Preallocated space for the gradient of size dim(parameters). Or gsl::span<double>() for evaluation without gradient.
logger – Optional Logger instance used for output
cputime – Optional output argument to report cpuTime consumed by the the function
- Returns:
Evaluation status
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inline virtual int numParameters() const override¶
Get dimension of function parameter vector.
- Returns:
Number of parameters
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inline virtual std::vector<std::string> getParameterIds() const override¶
Public Members
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int numParameters_ = 0¶
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std::vector<std::vector<double>> datasets¶
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std::vector<double> labels¶
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LinearModel lm¶
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inline explicit LinearModelMSE(int numParameters)¶