meta::classify::loss::loss_function Struct Reference

Base class for all loss functions that can be passed to the sgd classifier. More...

#include <loss_function.h>

Inheritance diagram for meta::classify::loss::loss_function:

Public Member Functions
virtual double	loss (double prediction, int expected) const =0
	The loss incurred in assigning the given prediction value, given the correct value of the prediction. More...
virtual double	derivative (double prediction, int expected) const =0
	The derivative of the loss function given a predicted value and the expected result of that prediction. More...

Detailed Description

Base class for all loss functions that can be passed to the sgd classifier.

Each loss function must specify the value of the loss for a given prediction vs. expected value, and also the derivative of the loss function for a given prediction vs. expected value.

See also

http://dl.acm.org/citation.cfm?id=1015332

Member Function Documentation

virtual double meta::classify::loss::loss_function::loss ( double  prediction, int  expected  ) const

pure virtual

The loss incurred in assigning the given prediction value, given the correct value of the prediction.

Parameters

prediction	The prediction obtained from the model (dot product)
expected	The expected (as in, correct) value of the model's prediction

Returns

the loss incurred

Implemented in meta::classify::loss::hinge, meta::classify::loss::huber, meta::classify::loss::logistic, meta::classify::loss::modified_huber, meta::classify::loss::smooth_hinge, meta::classify::loss::least_squares, meta::classify::loss::perceptron, and meta::classify::loss::squared_hinge.

virtual double meta::classify::loss::loss_function::derivative ( double  prediction, int  expected  ) const

pure virtual

The derivative of the loss function given a predicted value and the expected result of that prediction.

Parameters

prediction	The prediction obtained from the model (dot product)
expected	The expected (as in, correct) value of the model's prediction

Returns

the derivative of the loss function at that point

Implemented in meta::classify::loss::hinge, meta::classify::loss::huber, meta::classify::loss::logistic, meta::classify::loss::modified_huber, meta::classify::loss::smooth_hinge, meta::classify::loss::least_squares, meta::classify::loss::perceptron, and meta::classify::loss::squared_hinge.

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

• /home/chase/projects/meta/include/classify/loss/loss_function.h