small adjustment

2022-11-18 05:50:27 +01:00
parent e3034398b7
commit e93e980131
8 changed files with 293 additions and 287 deletions
@@ -1140,6 +1140,7 @@ sol = solvers.qp(P,q,G,h)
 # Extract optimal value and solution
 sol['x'] 
 sol['primal objective']
+print(sol['x'] )
 !ec

 !split
@@ -1160,7 +1161,7 @@ subject to $\bm{y}^T\bm{\lambda}=0$. Here we defined the vectors $\bm{\lambda} =
 $\bm{y}=[y_1,y_2,\dots,y_n]$. 
 With  the slack constants this leads to the additional constraint $0\leq \lambda_i \leq C$.

-Using the _CVXOPT_ library, the matrix $P$ would then be defined by the 
+Using the _CVXOPT_ library, the matrix $P$ would then be defined by the above matrix while the KKT conditions would all be collected by the matrix $G$.