Merge pull request #1681 from karlnapf/develop

speed ups for tests
shogun-toolbox · Sep 26, 2013 · f607173 · f607173
2 parents eff23a5 + 7f21c9b
commit f607173
Show file tree

Hide file tree

Showing 4 changed files with 12 additions and 10 deletions.
diff --git a/examples/undocumented/python_modular/mathematics_logdet.py b/examples/undocumented/python_modular/mathematics_logdet.py
@@ -6,7 +6,7 @@
 # Loading an example sparse matrix of dimension 479x479, real, unsymmetric
 mtx=mmread('../data/../logdet/west0479.mtx.gz')
 
-parameter_list=[[mtx,10000,6000,1]]
+parameter_list=[[mtx,100,60,1]]
 
 def mathematics_logdet (matrix=mtx,max_iter_eig=1000,max_iter_lin=1000,num_samples=1):
 

diff --git a/examples/undocumented/python_modular/modelselection_grid_search_krr_modular.py b/examples/undocumented/python_modular/modelselection_grid_search_krr_modular.py
@@ -56,8 +56,9 @@ def modelselection_grid_search_krr_modular (fm_train=traindat,fm_test=testdat,la
     cross_validation=CrossValidation(predictor, features_train, labels,
 	    splitting_strategy, evaluation_criterium)
 
-    # (optional) repeat x-val 10 times
-    cross_validation.set_num_runs(10)
+    # (optional) repeat x-val (set larger to get better estimates, at least two
+    # for confidence intervals)
+    cross_validation.set_num_runs(2)
 
     # (optional) request 95% confidence intervals for results (not actually needed
     # for this toy example)
@@ -122,7 +123,7 @@ def create_param_tree():
 
     param_gaussian_kernel=ModelSelectionParameters("kernel", gaussian_kernel)
     gaussian_kernel_width=ModelSelectionParameters("width");
-    gaussian_kernel_width.build_values(5.0, 8.0, R_EXP, 1.0, 2.0)
+    gaussian_kernel_width.build_values(5.0, 6.0, R_EXP, 1.0, 2.0)
     param_gaussian_kernel.append_child(gaussian_kernel_width)
     root.append_child(param_gaussian_kernel)
 

diff --git a/examples/undocumented/python_modular/modelselection_grid_search_liblinear_modular.py b/examples/undocumented/python_modular/modelselection_grid_search_liblinear_modular.py
@@ -36,11 +36,11 @@ def modelselection_grid_search_liblinear_modular (traindat=traindat, label_train
     param_tree_root=ModelSelectionParameters()
     c1=ModelSelectionParameters("C1");
     param_tree_root.append_child(c1)
-    c1.build_values(-2.0, 2.0, R_EXP);
+    c1.build_values(-1.0, 0.0, R_EXP);
 
     c2=ModelSelectionParameters("C2");
     param_tree_root.append_child(c2);
-    c2.build_values(-2.0, 2.0, R_EXP);
+    c2.build_values(-1.0, 0.0, R_EXP);
 
     # training data
     features=RealFeatures(traindat)

diff --git a/examples/undocumented/python_modular/modelselection_grid_search_libsvr_modular.py b/examples/undocumented/python_modular/modelselection_grid_search_libsvr_modular.py
@@ -64,8 +64,9 @@ def modelselection_grid_search_libsvr_modular (fm_train=traindat,fm_test=testdat
     cross_validation=CrossValidation(predictor, features_train, labels,
 	    splitting_strategy, evaluation_criterium)
 
-    # (optional) repeat x-val 10 times
-    cross_validation.set_num_runs(10)
+#	 (optional) repeat x-val (set larger to get better estimates, at least two
+    # for confidence intervals)
+    cross_validation.set_num_runs(2)
 
     # (optional) request 95% confidence intervals for results (not actually
     # needed for this toy example)
@@ -79,11 +80,11 @@ def modelselection_grid_search_libsvr_modular (fm_train=traindat,fm_test=testdat
     param_tree_root=ModelSelectionParameters()
     c1=ModelSelectionParameters("C1");
     param_tree_root.append_child(c1)
-    c1.build_values(-2.0, 2.0, R_EXP);
+    c1.build_values(-1.0, 0.0, R_EXP);
 
     c2=ModelSelectionParameters("C2");
     param_tree_root.append_child(c2);
-    c2.build_values(-2.0, 2.0, R_EXP);
+    c2.build_values(-1.0, 0.0, R_EXP);
 
     # model selection instance
     model_selection=GridSearchModelSelection(cross_validation, param_tree_root)