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Added some clarifying comments to the svm example and a version number to

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the about window in the bayes net gui.

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extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%402223
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Davis King 2008-05-10 18:53:10 +00:00
parent 0c356e015d
commit db3f3c17ae
2 changed files with 2 additions and 0 deletions
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examples/bayes_net_gui_ex.cpp
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@ -626,6 +626,7 @@ on_menu_help_about (
{ {
message_box("About","This application is the GUI front end to the dlib C++ Library's\n" message_box("About","This application is the GUI front end to the dlib C++ Library's\n"
"Bayesian Network inference utilities\n\n" "Bayesian Network inference utilities\n\n"
"Version 1.1\n\n"
"See http://dclib.sourceforge.net for updates"); "See http://dclib.sourceforge.net for updates");
} }

1
examples/svm_ex.cpp
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@ -144,6 +144,7 @@ int main()
// We can also train a decision function that reports a well conditioned probability instead of just a number // We can also train a decision function that reports a well conditioned probability instead of just a number
// > 0 for the +1 class and < 0 for the -1 class. An example of doing that follows: // > 0 for the +1 class and < 0 for the -1 class. An example of doing that follows:
probabilistic_decision_function<kernel_type> learned_probabilistic_decision_function = svm_nu_train_prob(samples, labels, kernel_type(0.1), 0.1, 3); probabilistic_decision_function<kernel_type> learned_probabilistic_decision_function = svm_nu_train_prob(samples, labels, kernel_type(0.1), 0.1, 3);
// Now we have a function that returns the probability that a given sample is of the +1 class.
// print out the number of support vectors in the resulting decision function. (it should be the same as in the one above) // print out the number of support vectors in the resulting decision function. (it should be the same as in the one above)
cout << "\nnumber of support vectors in our learned_probabilistic_decision_function is " cout << "\nnumber of support vectors in our learned_probabilistic_decision_function is "