You need to sign in or sign up before continuing.
Commit 176b3db2 authored by Davis King's avatar Davis King
Browse files

Added missing comment about the QP needing to be convex.

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403912
parent 97a37ae3
...@@ -28,6 +28,7 @@ namespace dlib ...@@ -28,6 +28,7 @@ namespace dlib
subject to the following constraints: subject to the following constraints:
- trans(e)*alpha == C (i.e. the sum of alpha values doesn't change) - trans(e)*alpha == C (i.e. the sum of alpha values doesn't change)
- min(alpha) >= 0 (i.e. all alpha values are nonnegative) - min(alpha) >= 0 (i.e. all alpha values are nonnegative)
Where f is convex. This means that Q should be positive-semidefinite.
To get from this problem formulation to the algorithm below we have to To get from this problem formulation to the algorithm below we have to
......
...@@ -40,6 +40,7 @@ namespace dlib ...@@ -40,6 +40,7 @@ namespace dlib
subject to the following constraints: subject to the following constraints:
- sum(alpha) == C (i.e. the sum of alpha values doesn't change) - sum(alpha) == C (i.e. the sum of alpha values doesn't change)
- min(alpha) >= 0 (i.e. all alpha values are nonnegative) - min(alpha) >= 0 (i.e. all alpha values are nonnegative)
Where f is convex. This means that Q should be positive-semidefinite.
- The solution to the above QP will be stored in #alpha. - The solution to the above QP will be stored in #alpha.
- This function uses a simple implementation of the sequential minimal - This function uses a simple implementation of the sequential minimal
optimization algorithm. It starts the algorithm with the given alpha optimization algorithm. It starts the algorithm with the given alpha
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment