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| author | jeanpouget-abadie <jean.pougetabadie@gmail.com> | 2015-02-04 14:05:47 -0500 |
|---|---|---|
| committer | jeanpouget-abadie <jean.pougetabadie@gmail.com> | 2015-02-04 14:05:47 -0500 |
| commit | 71cf5d890df71701d0fd60f1907a1cc63b508cbf (patch) | |
| tree | 9acbdf7ee08d1ceba8b15e4eac169680ab77bb82 /src/convex_optimization.py | |
| parent | a819813ca6c310d84a52de51e7bc49ea8dd8a726 (diff) | |
| download | cascades-71cf5d890df71701d0fd60f1907a1cc63b508cbf.tar.gz | |
adding precision_recall curve
Diffstat (limited to 'src/convex_optimization.py')
| -rw-r--r-- | src/convex_optimization.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/src/convex_optimization.py b/src/convex_optimization.py index 0ff4521..e355bc6 100644 --- a/src/convex_optimization.py +++ b/src/convex_optimization.py @@ -80,7 +80,7 @@ def type_lasso(lbda, n_cascades): return f_x, f_xz -@timeout.timeout(70) +@timeout.timeout(10) def diff_and_opt(M_val, w_val, f_x, f_xz): if M_val.dtype == bool: @@ -90,7 +90,7 @@ def diff_and_opt(M_val, w_val, f_x, f_xz): def F(x=None, z=None): if x is None: - return 0, cvxopt.matrix(-.1, (n,1)) + return 0, cvxopt.matrix(-.001, (n,1)) elif z is None: y, y_diff = f_x(x, M_val, w_val) return cvxopt.matrix(float(y), (1, 1)),\ |