Merge pull request #227 from karlnapf/master

simplified parameter trees for model selection
shogun-toolbox · Jul 22, 2011 · 31d21d3 · 31d21d3
2 parents 0f1f5d9 + 80b7302
commit 31d21d3
Show file tree

Hide file tree

Showing 9 changed files with 24 additions and 138 deletions.
diff --git a/examples/undocumented/libshogun/modelselection_apply_parameter_tree.cpp b/examples/undocumented/libshogun/modelselection_apply_parameter_tree.cpp
@@ -27,9 +27,6 @@ CModelSelectionParameters* create_param_tree()
 {
 	CModelSelectionParameters* root=new CModelSelectionParameters();
 
-	CModelSelectionParameters* kernel=new CModelSelectionParameters("kernel");
-	root->append_child(kernel);
-
 	CModelSelectionParameters* c=new CModelSelectionParameters("C1");
 	root->append_child(c);
 	c->build_values(1, 2, R_EXP);
@@ -38,7 +35,7 @@ CModelSelectionParameters* create_param_tree()
 	CModelSelectionParameters* param_gaussian_kernel=
 			new CModelSelectionParameters("kernel", gaussian_kernel);
 
-	kernel->append_child(param_gaussian_kernel);
+	root->append_child(param_gaussian_kernel);
 
 	CModelSelectionParameters* param_gaussian_kernel_width=
 			new CModelSelectionParameters("width");

diff --git a/examples/undocumented/libshogun/modelselection_model_selection_parameters_test.cpp b/examples/undocumented/libshogun/modelselection_model_selection_parameters_test.cpp
@@ -27,9 +27,6 @@ CModelSelectionParameters* build_complex_example_tree()
 {
 	CModelSelectionParameters* root=new CModelSelectionParameters();
 
-	CModelSelectionParameters* kernel=new CModelSelectionParameters("kernel");
-	root->append_child(kernel);
-
 	CModelSelectionParameters* c=new CModelSelectionParameters("C");
 	root->append_child(c);
 	c->build_values(1, 1, R_EXP);
@@ -38,7 +35,7 @@ CModelSelectionParameters* build_complex_example_tree()
 	CModelSelectionParameters* param_power_kernel=
 			new CModelSelectionParameters("kernel", power_kernel);
 
-	kernel->append_child(param_power_kernel);
+	root->append_child(param_power_kernel);
 
 	CModelSelectionParameters* param_power_kernel_degree=
 			new CModelSelectionParameters("degree");
@@ -60,7 +57,7 @@ CModelSelectionParameters* build_complex_example_tree()
 	CModelSelectionParameters* param_gaussian_kernel=
 			new CModelSelectionParameters("kernel", gaussian_kernel);
 
-	kernel->append_child(param_gaussian_kernel);
+	root->append_child(param_gaussian_kernel);
 
 	CModelSelectionParameters* param_gaussian_kernel_width=
 			new CModelSelectionParameters("width");
@@ -71,7 +68,7 @@ CModelSelectionParameters* build_complex_example_tree()
 	CModelSelectionParameters* param_ds_kernel=new CModelSelectionParameters("kernel",
 			ds_kernel);
 
-	kernel->append_child(param_ds_kernel);
+	root->append_child(param_ds_kernel);
 
 	CModelSelectionParameters* param_ds_kernel_delta=
 			new CModelSelectionParameters("delta");
@@ -108,19 +105,6 @@ CModelSelectionParameters* build_root_no_childs_tree()
 	return new CModelSelectionParameters();
 }
 
-CModelSelectionParameters* build_name_node_one_child_tree()
-{
-	CModelSelectionParameters* kernel=new CModelSelectionParameters("kernel");
-
-	CPowerKernel* power_kernel=new CPowerKernel();
-	CModelSelectionParameters* param_power_kernel=new CModelSelectionParameters(
-			"kernel", power_kernel);
-
-	kernel->append_child(param_power_kernel);
-
-	return kernel;
-}
-
 CModelSelectionParameters* build_root_value_childs_tree()
 {
 	CModelSelectionParameters* root=new CModelSelectionParameters();
@@ -136,29 +120,23 @@ CModelSelectionParameters* build_root_value_childs_tree()
 	return root;
 }
 
-CModelSelectionParameters* build_root_name_sg_object_child_tree()
+CModelSelectionParameters* build_root_sg_object_child_tree()
 {
 	CModelSelectionParameters* root=new CModelSelectionParameters();
 
-	CModelSelectionParameters* kernel=new CModelSelectionParameters("kernel");
-		root->append_child(kernel);
-
 	CPowerKernel* power_kernel=new CPowerKernel();
 	CModelSelectionParameters* param_power_kernel=
 			new CModelSelectionParameters("kernel", power_kernel);
 
-	kernel->append_child(param_power_kernel);
+	root->append_child(param_power_kernel);
 
 	return root;
 }
 
-CModelSelectionParameters* build_root_name_sg_object_child_value_child_tree()
+CModelSelectionParameters* build_root_sg_object_child_value_child_tree()
 {
 	CModelSelectionParameters* root=new CModelSelectionParameters();
 
-	CModelSelectionParameters* kernel=new CModelSelectionParameters("kernel");
-		root->append_child(kernel);
-
 	CPowerKernel* power_kernel=new CPowerKernel();
 	CModelSelectionParameters* param_power_kernel=
 			new CModelSelectionParameters("kernel", power_kernel);
@@ -167,7 +145,7 @@ CModelSelectionParameters* build_root_name_sg_object_child_value_child_tree()
 	root->append_child(c);
 	c->build_values(1, 1, R_EXP);
 
-	kernel->append_child(param_power_kernel);
+	root->append_child(param_power_kernel);
 
 	return root;
 }
@@ -212,22 +190,17 @@ int main(int argc, char **argv)
 	test_get_combinations(tree);
 	SG_UNREF(tree);
 
-	tree=build_name_node_one_child_tree();
-	SG_REF(tree);
-	test_get_combinations(tree);
-	SG_UNREF(tree);
-
 	tree=build_root_value_childs_tree();
 	SG_REF(tree);
 	test_get_combinations(tree);
 	SG_UNREF(tree);
 
-	tree=build_root_name_sg_object_child_tree();
+	tree=build_root_sg_object_child_tree();
 	SG_REF(tree);
 	test_get_combinations(tree);
 	SG_UNREF(tree);
 
-	tree=build_root_name_sg_object_child_value_child_tree();
+	tree=build_root_sg_object_child_value_child_tree();
 	SG_REF(tree);
 	test_get_combinations(tree);
 	SG_UNREF(tree);

diff --git a/examples/undocumented/libshogun/modelselection_parameter_tree.cpp b/examples/undocumented/libshogun/modelselection_parameter_tree.cpp
@@ -27,9 +27,6 @@ CModelSelectionParameters* create_param_tree()
 {
 	CModelSelectionParameters* root=new CModelSelectionParameters();
 
-	CModelSelectionParameters* kernel=new CModelSelectionParameters("kernel");
-	root->append_child(kernel);
-
 	CModelSelectionParameters* c=new CModelSelectionParameters("C");
 	root->append_child(c);
 	c->build_values(1, 11, R_EXP);
@@ -38,7 +35,7 @@ CModelSelectionParameters* create_param_tree()
 	CModelSelectionParameters* param_power_kernel=
 			new CModelSelectionParameters("kernel", power_kernel);
 
-	kernel->append_child(param_power_kernel);
+	root->append_child(param_power_kernel);
 
 	CModelSelectionParameters* param_power_kernel_degree=
 			new CModelSelectionParameters("degree");
@@ -60,7 +57,7 @@ CModelSelectionParameters* create_param_tree()
 	CModelSelectionParameters* param_gaussian_kernel=
 			new CModelSelectionParameters("kernel", gaussian_kernel);
 
-	kernel->append_child(param_gaussian_kernel);
+	root->append_child(param_gaussian_kernel);
 
 	CModelSelectionParameters* param_gaussian_kernel_width=
 			new CModelSelectionParameters("width");
@@ -71,7 +68,7 @@ CModelSelectionParameters* create_param_tree()
 	CModelSelectionParameters* param_ds_kernel=new CModelSelectionParameters("kernel",
 			ds_kernel);
 
-	kernel->append_child(param_ds_kernel);
+	root->append_child(param_ds_kernel);
 
 	CModelSelectionParameters* param_ds_kernel_delta=
 			new CModelSelectionParameters("delta");

diff --git a/examples/undocumented/python_modular/modelselection_parameter_tree_modular.py b/examples/undocumented/python_modular/modelselection_parameter_tree_modular.py
@@ -22,16 +22,13 @@ def modelselection_parameter_tree_modular():
 	combinations=root.get_combinations()
 	combinations.get_num_elements()
 
-	kernel=ModelSelectionParameters('kernel')
-	root.append_child(kernel)
-
 	c=ModelSelectionParameters('C');
 	root.append_child(c)
 	c.build_values(1, 11, R_EXP)
 
 	power_kernel=PowerKernel()
 	param_power_kernel=ModelSelectionParameters('kernel', power_kernel)
-	kernel.append_child(param_power_kernel)
+	root.append_child(param_power_kernel)
 
 	param_power_kernel_degree=ModelSelectionParameters('degree')
 	param_power_kernel_degree.build_values(1, 1, R_EXP)
@@ -49,7 +46,7 @@ def modelselection_parameter_tree_modular():
 	gaussian_kernel=GaussianKernel()
 	param_gaussian_kernel=ModelSelectionParameters('kernel', gaussian_kernel)
 
-	kernel.append_child(param_gaussian_kernel)
+	root.append_child(param_gaussian_kernel)
 
 	param_gaussian_kernel_width=ModelSelectionParameters('width')
 	param_gaussian_kernel_width.build_values(1, 2, R_EXP)
@@ -58,7 +55,7 @@ def modelselection_parameter_tree_modular():
 	ds_kernel=DistantSegmentsKernel()
 	param_ds_kernel=ModelSelectionParameters('kernel', ds_kernel)
 
-	kernel.append_child(param_ds_kernel)
+	root.append_child(param_ds_kernel)
 
 	param_ds_kernel_delta=ModelSelectionParameters('delta')
 	param_ds_kernel_delta.build_values(1, 2, R_EXP)

diff --git a/src/shogun/evaluation/CrossValidation.cpp b/src/shogun/evaluation/CrossValidation.cpp
@@ -13,6 +13,7 @@
 #include <shogun/evaluation/Evaluation.h>
 #include <shogun/evaluation/SplittingStrategy.h>
 #include <shogun/base/Parameter.h>
+#include <shogun/mathematics/Statistics.h>
 
 using namespace shogun;
 
@@ -86,7 +87,7 @@ CrossValidationResult CCrossValidation::evaluate()
 
 	/* construct evaluation result */
 	CrossValidationResult result;
-	result.value=CMath::mean(results, m_num_runs);
+	result.value=CStatistics::mean(SGVector<float64_t>(results, m_num_runs));
 	result.has_conf_int=m_conf_int_p!=0;
 	result.conf_int_p=m_conf_int_p;
 
@@ -178,7 +179,7 @@ float64_t CCrossValidation::evaluate_one_run()
 	}
 
 	/* build arithmetic mean of results */
-	float64_t mean=CMath::mean(results, num_subsets);
+	float64_t mean=CStatistics::mean(SGVector<float64_t>(results, num_subsets));
 
 	/* clean up */
 	delete[] results;

diff --git a/src/shogun/modelselection/ModelSelectionParameters.cpp b/src/shogun/modelselection/ModelSelectionParameters.cpp
@@ -86,10 +86,6 @@ void CModelSelectionParameters::append_child(CModelSelectionParameters* child)
 		}
 	}
 
-	/* root nodes may not have sgobject children */
-	if (!m_node_name && !has_children() && child->m_sgobject)
-		SG_ERROR("root node may not have CSGObject children\n");
-
 	m_child_nodes->append_element(child);
 }
 
@@ -341,52 +337,6 @@ CDynamicObjectArray<CParameterCombination>* CModelSelectionParameters::get_combi
 		}
 
 	}
-
-	/* case name placeholder node: a node which contains a (parameter) name and
-	 * one (or more) CSGObject nodes which are to be substituted into the
-	 * parameter with the above name. The parameter name is one of the learning
-	 * machine, like "kernel". basically all combinations of all children have to
-	 * be appended to the result and a new root is to be added to all trees
-	 */
-	else if (m_node_name && !m_sgobject && !m_values.vector)
-	{
-		if (!m_child_nodes->get_num_elements())
-		{
-			SG_ERROR("ModelSelectionParameter node with name but no children or "
-					"values.\n");
-		}
-
-		for (index_t i=0; i<m_child_nodes->get_num_elements(); ++i)
-		{
-			/* recursively get all combinations of the current child */
-			CModelSelectionParameters* child=m_child_nodes->get_element(i);
-			CDynamicObjectArray<CParameterCombination>* child_combinations=
-					child->get_combinations();
-			SG_REF(child_combinations);
-
-			SG_UNREF(child);
-
-			/* and process them each */
-			for (index_t j=0; j<child_combinations->get_num_elements(); ++j)
-			{
-				CParameterCombination* current=child_combinations->get_element(
-						j);
-
-				/* append new root node with the name */
-				CParameterCombination* new_root=new CParameterCombination(
-						m_node_name);
-				new_root->append_child(current);
-				child_combinations->set_element(new_root, j);
-
-				SG_UNREF(current);
-
-				/* append them to the result */
-				result->append_element(new_root);
-			}
-
-			SG_UNREF(child_combinations);
-		}
-	}
 	else
 		SG_ERROR("Illegal CModelSelectionParameters node type.\n");
 

diff --git a/src/shogun/modelselection/ModelSelectionParameters.h b/src/shogun/modelselection/ModelSelectionParameters.h
@@ -29,11 +29,7 @@ enum ERangeType
  * structure is organized as a tree with different kinds of nodes, depending on
  * the values of its member variables of name and CSGObject.
  *
- * -root node: no name and no CSGObject, may have children. Children may not be
- * of CSGObject node type (use placeholder node)
- *
- * -placeholder node: only has a name and children, used to bundle parameters
- * that belong to the learning machine directly, like "kernel"
+ * -root node: no name and no CSGObject, may have children
  *
  * -CSGObject node: has name and a CSGObject, may have children which are the
  * parameters of the CSGObject. CSGObjects are SG_REF'ed/SG_UNREF'ed
@@ -45,7 +41,7 @@ enum ERangeType
  * After a (legal!) tree is constructed with the append_child method, all
  * possible combinations that are implied by this tree may be extracted with the
  * get_combinations method. It generates a set of trees (different kind than
- * this one) that contain the instanciated parameter combinations.
+ * this one) that contain the instantiated parameter combinations.
  */
 class CModelSelectionParameters: public CSGObject
 {
@@ -80,9 +76,6 @@ class CModelSelectionParameters: public CSGObject
 	 * ERangeType (s. above) of the range, which is used to fill an array with
 	 * concrete values. For some range types, a base is required
 	 *
-	 * Calling this function transforms a placeholder node (without children)
-	 * into a value node.
-	 *
 	 * @param min minimum of desired range. Requires min<max
 	 * @param max maximum of desired range. Requires min<max
 	 * @param type the way the values are created, see ERangeType