mirror of https://github.com/davisking/dlib.git
Added missing get/set epsilon functions to the RVM training objects.
I also changed the default epsilon from 0.0005 to 0.001. --HG-- extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403777
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@ -147,10 +147,29 @@ namespace dlib
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typedef decision_function<kernel_type> trained_function_type;
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rvm_trainer (
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) : eps(0.0005)
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) : eps(0.001)
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{
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}
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void set_epsilon (
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scalar_type eps_
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)
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{
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// make sure requires clause is not broken
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DLIB_ASSERT(eps_ > 0,
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"\tvoid rvm_trainer::set_epsilon(eps_)"
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<< "\n\t invalid inputs were given to this function"
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<< "\n\t eps: " << eps_
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);
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eps = eps_;
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}
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const scalar_type get_epsilon (
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) const
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{
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return eps;
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}
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void set_kernel (
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const kernel_type& k
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)
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@ -600,10 +619,29 @@ namespace dlib
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typedef decision_function<kernel_type> trained_function_type;
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rvm_regression_trainer (
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) : eps(0.0005)
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) : eps(0.001)
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{
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}
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void set_epsilon (
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scalar_type eps_
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)
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{
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// make sure requires clause is not broken
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DLIB_ASSERT(eps_ > 0,
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"\tvoid rvm_regression_trainer::set_epsilon(eps_)"
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<< "\n\t invalid inputs were given to this function"
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<< "\n\t eps: " << eps_
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);
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eps = eps_;
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}
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const scalar_type get_epsilon (
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) const
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{
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return eps;
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}
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void set_kernel (
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const kernel_type& k
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)
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@ -49,6 +49,26 @@ namespace dlib
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ensures
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- This object is properly initialized and ready to be used
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to train a relevance vector machine.
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- #get_epsilon() == 0.001
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!*/
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void set_epsilon (
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scalar_type eps
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);
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/*!
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requires
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- eps > 0
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ensures
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- #get_epsilon() == eps
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!*/
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const scalar_type get_epsilon (
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) const;
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/*!
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ensures
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- returns the error epsilon that determines when training should stop.
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Generally a good value for this is 0.001. Smaller values may result
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in a more accurate solution but take longer to execute.
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!*/
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void set_kernel (
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@ -152,6 +172,26 @@ namespace dlib
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ensures
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- This object is properly initialized and ready to be used
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to train a relevance vector machine.
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- #get_epsilon() == 0.001
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!*/
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void set_epsilon (
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scalar_type eps
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);
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/*!
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requires
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- eps > 0
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ensures
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- #get_epsilon() == eps
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!*/
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const scalar_type get_epsilon (
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) const;
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/*!
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ensures
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- returns the error epsilon that determines when training should stop.
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Generally a good value for this is 0.001. Smaller values may result
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in a more accurate solution but take longer to execute.
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!*/
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void set_kernel (
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