From f710b18b460a3ff2d4bc4d6c16cf460c66fc24cb Mon Sep 17 00:00:00 2001 From: Davis King Date: Thu, 23 Dec 2010 22:55:45 +0000 Subject: [PATCH] Clarified spec --HG-- extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%404024 --- dlib/svm/krr_trainer_abstract.h | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/dlib/svm/krr_trainer_abstract.h b/dlib/svm/krr_trainer_abstract.h index d9f190f21..66f5f9c35 100644 --- a/dlib/svm/krr_trainer_abstract.h +++ b/dlib/svm/krr_trainer_abstract.h @@ -33,7 +33,7 @@ namespace dlib least squares or least squares SVM). 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 ) where f(x) == dot(x,w) - b @@ -240,7 +240,7 @@ namespace dlib classification functions then you had better give a valid classification problem) 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: - F(new_x) == predicted y value