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Davis King 2010-12-23 22:55:45 +00:00
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dlib/svm/krr_trainer_abstract.h
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@ -33,7 +33,7 @@ namespace dlib
least squares or least squares SVM). least squares or least squares SVM).
The exact definition of what this algorithm does is this: The exact definition of what this algorithm does is this:
Find w and b that minimizes the following (x_i are input samples and y_i are labels): Find w and b that minimizes the following (x_i are input samples and y_i are target values):
lambda*dot(w,w) + sum_over_i( (f(x_i) - y_i)^2 ) lambda*dot(w,w) + sum_over_i( (f(x_i) - y_i)^2 )
where f(x) == dot(x,w) - b where f(x) == dot(x,w) - b
@ -240,7 +240,7 @@ namespace dlib
classification functions then you had better give a valid classification classification functions then you had better give a valid classification
problem) problem)
ensures ensures
- performs kernel ridge regression given the training samples in x and labels in y. - performs kernel ridge regression given the training samples in x and target values in y.
- returns a decision_function F with the following properties: - returns a decision_function F with the following properties:
- F(new_x) == predicted y value - F(new_x) == predicted y value