Merge pull request #366 from karlnapf/master

added print_modsel_params method
shogun-toolbox · Feb 3, 2012 · 1778466 · 1778466
2 parents 3a9377d + 269dbf9
commit 1778466
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Showing 18 changed files with 327 additions and 108 deletions.
diff --git a/examples/undocumented/libshogun/modelselection_apply_parameter_tree.cpp b/examples/undocumented/libshogun/modelselection_apply_parameter_tree.cpp
@@ -32,6 +32,11 @@ CModelSelectionParameters* create_param_tree()
 	c->build_values(1.0, 2.0, R_EXP);
 
 	CGaussianKernel* gaussian_kernel=new CGaussianKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	gaussian_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_gaussian_kernel=
 			new CModelSelectionParameters("kernel", gaussian_kernel);
 

diff --git a/examples/undocumented/libshogun/modelselection_grid_search_kernel.cpp b/examples/undocumented/libshogun/modelselection_grid_search_kernel.cpp
@@ -43,6 +43,11 @@ CModelSelectionParameters* create_param_tree()
 	c2->build_values(-1.0, 1.0, R_EXP);
 
 	CGaussianKernel* gaussian_kernel=new CGaussianKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	gaussian_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_gaussian_kernel=
 			new CModelSelectionParameters("kernel", gaussian_kernel);
 	CModelSelectionParameters* gaussian_kernel_width=
@@ -52,6 +57,11 @@ CModelSelectionParameters* create_param_tree()
 	root->append_child(param_gaussian_kernel);
 
 	CPowerKernel* power_kernel=new CPowerKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	power_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_power_kernel=
 	new CModelSelectionParameters("kernel", power_kernel);
 
@@ -63,6 +73,11 @@ CModelSelectionParameters* create_param_tree()
 	param_power_kernel->append_child(param_power_kernel_degree);
 
 	CMinkowskiMetric* m_metric=new CMinkowskiMetric(10);
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	m_metric->print_modsel_params();
+
 	CModelSelectionParameters* param_power_kernel_metric1=
 			new CModelSelectionParameters("distance", m_metric);
 
@@ -114,6 +129,10 @@ int main(int argc, char **argv)
 			splitting_strategy, evaluation_criterium);
 	cross->set_num_runs(1);
 
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	classifier->print_modsel_params();
+
 	/* model parameter selection, deletion is handled by modsel class (SG_UNREF) */
 	CModelSelectionParameters* param_tree=create_param_tree();
 	param_tree->print_tree();

diff --git a/examples/undocumented/libshogun/modelselection_grid_search_krr.cpp b/examples/undocumented/libshogun/modelselection_grid_search_krr.cpp
@@ -37,6 +37,11 @@ CModelSelectionParameters* create_param_tree()
 	tau->build_values(-1.0, 1.0, R_EXP);
 
 	CGaussianKernel* gaussian_kernel=new CGaussianKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	gaussian_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_gaussian_kernel=
 			new CModelSelectionParameters("kernel", gaussian_kernel);
 	CModelSelectionParameters* gaussian_kernel_width=
@@ -46,6 +51,11 @@ CModelSelectionParameters* create_param_tree()
 	root->append_child(param_gaussian_kernel);
 
 	CPolyKernel* poly_kernel=new CPolyKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	poly_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_poly_kernel=
 	new CModelSelectionParameters("kernel", poly_kernel);
 
@@ -105,6 +115,10 @@ void test_cross_validation()
 	cross->set_num_runs(3);
 	cross->set_conf_int_alpha(0.05);
 
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	krr->print_modsel_params();
+
 	/* model parameter selection, deletion is handled by modsel class (SG_UNREF) */
 	CModelSelectionParameters* param_tree=create_param_tree();
 	param_tree->print_tree();

diff --git a/examples/undocumented/libshogun/modelselection_grid_search_linear.cpp b/examples/undocumented/libshogun/modelselection_grid_search_linear.cpp
@@ -79,6 +79,11 @@ int main(int argc, char **argv)
 	CCrossValidation* cross=new CCrossValidation(classifier, features, labels,
 			splitting_strategy, evaluation_criterium);
 
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	classifier->print_modsel_params();
+
+
 	/* model parameter selection, deletion is handled by modsel class (SG_UNREF) */
 	CModelSelectionParameters* param_tree=create_param_tree();
 	param_tree->print_tree();

diff --git a/examples/undocumented/libshogun/modelselection_grid_search_string_kernel.cpp b/examples/undocumented/libshogun/modelselection_grid_search_string_kernel.cpp
@@ -41,6 +41,12 @@ CModelSelectionParameters* create_param_tree()
 	c2->build_values(1.0, 2.0, R_EXP);
 
 	CDistantSegmentsKernel* ds_kernel=new CDistantSegmentsKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	ds_kernel->print_modsel_params();
+
+
 	CModelSelectionParameters* param_ds_kernel=
 			new CModelSelectionParameters("kernel", ds_kernel);
 	root->append_child(param_ds_kernel);
@@ -116,6 +122,10 @@ int main(int argc, char **argv)
 			splitting_strategy, evaluation_criterium);
 	cross->set_num_runs(2);
 
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	classifier->print_modsel_params();
+
 	/* model parameter selection, deletion is handled by modsel class (SG_UNREF) */
 	CModelSelectionParameters* param_tree=create_param_tree();
 	param_tree->print_tree();

diff --git a/examples/undocumented/libshogun/modelselection_model_selection_parameters_test.cpp b/examples/undocumented/libshogun/modelselection_model_selection_parameters_test.cpp
@@ -32,6 +32,11 @@ CModelSelectionParameters* build_complex_example_tree()
 	c->build_values(1.0, 1.0, R_EXP);
 
 	CPowerKernel* power_kernel=new CPowerKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	power_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_power_kernel=
 			new CModelSelectionParameters("kernel", power_kernel);
 
@@ -54,6 +59,11 @@ CModelSelectionParameters* build_complex_example_tree()
 	param_power_kernel_metric1->append_child(param_power_kernel_metric1_k);
 
 	CGaussianKernel* gaussian_kernel=new CGaussianKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	gaussian_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_gaussian_kernel=
 			new CModelSelectionParameters("kernel", gaussian_kernel);
 
@@ -65,6 +75,11 @@ CModelSelectionParameters* build_complex_example_tree()
 	param_gaussian_kernel->append_child(param_gaussian_kernel_width);
 
 	CDistantSegmentsKernel* ds_kernel=new CDistantSegmentsKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	ds_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_ds_kernel=new CModelSelectionParameters("kernel",
 			ds_kernel);
 
@@ -125,6 +140,11 @@ CModelSelectionParameters* build_root_sg_object_child_tree()
 	CModelSelectionParameters* root=new CModelSelectionParameters();
 
 	CPowerKernel* power_kernel=new CPowerKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	power_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_power_kernel=
 			new CModelSelectionParameters("kernel", power_kernel);
 
@@ -138,6 +158,11 @@ CModelSelectionParameters* build_root_sg_object_child_value_child_tree()
 	CModelSelectionParameters* root=new CModelSelectionParameters();
 
 	CPowerKernel* power_kernel=new CPowerKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	power_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_power_kernel=
 			new CModelSelectionParameters("kernel", power_kernel);
 

diff --git a/examples/undocumented/libshogun/modelselection_parameter_tree.cpp b/examples/undocumented/libshogun/modelselection_parameter_tree.cpp
@@ -32,6 +32,11 @@ CModelSelectionParameters* create_param_tree()
 	c->build_values(1, 2, R_EXP);
 
 	CPowerKernel* power_kernel=new CPowerKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	power_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_power_kernel=
 			new CModelSelectionParameters("kernel", power_kernel);
 
@@ -43,6 +48,11 @@ CModelSelectionParameters* create_param_tree()
 	param_power_kernel->append_child(param_power_kernel_degree);
 
 	CMinkowskiMetric* m_metric=new CMinkowskiMetric(10);
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	m_metric->print_modsel_params();
+
 	CModelSelectionParameters* param_power_kernel_metric1=
 			new CModelSelectionParameters("distance", m_metric);
 
@@ -54,6 +64,11 @@ CModelSelectionParameters* create_param_tree()
 	param_power_kernel_metric1->append_child(param_power_kernel_metric1_k);
 
 	CGaussianKernel* gaussian_kernel=new CGaussianKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	gaussian_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_gaussian_kernel=
 			new CModelSelectionParameters("kernel", gaussian_kernel);
 
@@ -65,6 +80,11 @@ CModelSelectionParameters* create_param_tree()
 	param_gaussian_kernel->append_child(param_gaussian_kernel_width);
 
 	CDistantSegmentsKernel* ds_kernel=new CDistantSegmentsKernel();
+
+	/* print all parameter available for modelselection
+	 * Dont worry if yours is not included, simply write to the mailing list */
+	ds_kernel->print_modsel_params();
+
 	CModelSelectionParameters* param_ds_kernel=new CModelSelectionParameters("kernel",
 			ds_kernel);
 

diff --git a/examples/undocumented/python_modular/evaluation_meansquaredlogerror_modular.py b/examples/undocumented/python_modular/evaluation_meansquaredlogerror_modular.py
@@ -0,0 +1,29 @@
+from tools.load import LoadMatrix
+from numpy import random
+lm=LoadMatrix()
+
+N = 100
+
+random.seed(17)
+ground_truth = abs(random.randn(N))
+predicted = abs(random.randn(N))
+
+parameter_list = [[ground_truth,predicted]]
+
+def evaluation_meansquarederror_modular(ground_truth, predicted):
+	from shogun.Features import Labels
+	from shogun.Evaluation import MeanSquaredLogError
+
+	ground_truth_labels = Labels(ground_truth)
+	predicted_labels = Labels(predicted)
+
+	evaluator = MeanSquaredLogError()
+	mse = evaluator.evaluate(predicted_labels,ground_truth_labels)
+
+	return mse
+
+
+if __name__=='__main__':
+	print 'MeanSquaredLogError'
+	evaluation_meansquarederror_modular(*parameter_list[0])
+
diff --git a/examples/undocumented/python_modular/modelselection_grid_search_krr.py b/examples/undocumented/python_modular/modelselection_grid_search_krr.py
@@ -62,17 +62,20 @@ def evaluation_cross_validation_classification(fm_train=traindat,fm_test=testdat
     # for this toy example)
     cross_validation.set_conf_int_alpha(0.05)
 
+    # print all parameter available for modelselection
+    # Dont worry if yours is not included but, write to the mailing list
+    predictor.print_modsel_params("\t")
+
     # build parameter tree to select regularization parameter
     param_tree_root=create_param_tree()
-
 
     # model selection instance
     model_selection=GridSearchModelSelection(param_tree_root,
 	    cross_validation)
 
     # perform model selection with selected methods
     #print "performing model selection of"
-    print "parameter tree"
+    print "parameter tree:"
     param_tree_root.print_tree()
 
     print "starting model selection"
@@ -110,6 +113,11 @@ def create_param_tree():
 
     # gaussian kernel with width
     gaussian_kernel=GaussianKernel()
+
+    # print all parameter available for modelselection
+    # Dont worry if yours is not included but, write to the mailing list
+    gaussian_kernel.print_modsel_params()
+
     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)
@@ -118,6 +126,11 @@ def create_param_tree():
 
     # polynomial kernel with degree
     poly_kernel=PolyKernel()
+
+    # print all parameter available for modelselection
+    # Dont worry if yours is not included but, write to the mailing list
+    poly_kernel.print_modsel_params()
+
     param_poly_kernel=ModelSelectionParameters("kernel", poly_kernel)
 
     root.append_child(param_poly_kernel)