port custom kernel meta example

shogun-toolbox · May 9, 2018 · fbaa510 · fbaa510
1 parent 54e6d3a
commit fbaa510
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Showing 6 changed files with 63 additions and 30 deletions.
diff --git a/data b/data
diff --git a/examples/meta/src/base_api/factory.sg b/examples/meta/src/base_api/factory.sg
@@ -1,12 +1,19 @@
+RealMatrix real_matrix(2,2)
+
 Machine lib_svm = machine("LibSVM")
 Machine lda = machine("LDA")
 Kernel kernel_gaussian = kernel("GaussianKernel")
 Kernel kernel_linear = kernel("LinearKernel")
 Kernel kernel_from_object = kernel(kernel_gaussian)
+Kernel kernel_custom_from_matrix = kernel(real_matrix)
 
-RealMatrix real_matrix(2,2)
 Features features_from_matrix = features(real_matrix)
 
+IntVector dims(2)
+dims[0] = 0
+dims[1] = 1
+Features features_with_subset = features_subset(features_from_matrix, dims)
+
 File features_file = csv_file("../../data/classifier_binary_2d_nonlinear_features_train.dat")
 Features features_from_file = features(features_file)
 

diff --git a/examples/meta/src/kernel/custom_kernel_machine.sg b/examples/meta/src/kernel/custom_kernel_machine.sg
@@ -0,0 +1,39 @@
+File f_feats_train = csv_file("../../data/classifier_binary_2d_nonlinear_features_train.dat")
+File f_feats_test = csv_file("../../data/classifier_binary_2d_nonlinear_features_test.dat")
+File f_labels_train = csv_file("../../data/classifier_binary_2d_nonlinear_labels_train.dat")
+File f_labels_test = csv_file("../../data/classifier_binary_2d_nonlinear_labels_test.dat")
+
+#![create_features]
+Features features_train = features(f_feats_train)
+Features features_test = features(f_feats_test)
+Labels labels_train = labels(f_labels_train)
+Labels labels_test = labels(f_labels_test)
+#![create_features]
+
+#![create_kernel]
+Kernel k_obj = kernel("GaussianKernel", log_width=1.0)
+k_obj.init(features_train, features_train)
+RealMatrix km_train = k_obj.get_kernel_matrix()
+k_obj.init(features_train, features_test)
+RealMatrix km_test = k_obj.get_kernel_matrix()
+Kernel k_train = kernel(km_train)
+Kernel k_test = kernel(km_test)
+#![create_kernel]
+
+#![create_machine]
+Machine svm = machine("LibSVM", C1=1.0, C2=1.0, kernel=k_train, labels=labels_train, epsilon=0.001)
+#![create_machine]
+
+#![train_and_apply]
+svm.train()
+svm.put("kernel", k_test)
+Labels labels_predict = svm.apply()
+RealVector labels = labels_predict.get_real_vector("labels")
+#![train_and_apply]
+
+#![evaluate_accuracy]
+Evaluation eval = evaluation("AccuracyMeasure")
+real accuracy = eval.evaluate(labels_predict, labels_test)
+#![evaluate_accuracy]
+
+
diff --git a/examples/undocumented/python/classifier_custom_kernel.py b/examples/undocumented/python/classifier_custom_kernel.py
diff --git a/src/interfaces/swig/shogun.i b/src/interfaces/swig/shogun.i
@@ -253,4 +253,8 @@ PUT_ADD(CECOCEncoder)
 PUT_ADD(CECOCDecoder)
 PUT_ADD(CMulticlassStrategy)
 
+%template(kernel) kernel<float64_t, float64_t>;
+%template(features) features<float64_t>;
+
+
 } // namespace shogun
diff --git a/src/shogun/util/factory.h b/src/shogun/util/factory.h
@@ -13,13 +13,13 @@
 #include <shogun/features/DenseSubsetFeatures.h>
 #include <shogun/io/CSVFile.h>
 #include <shogun/io/SGIO.h>
+#include <shogun/kernel/CustomKernel.h>
 #include <shogun/kernel/Kernel.h>
 #include <shogun/labels/DenseLabels.h>
 #include <shogun/machine/Machine.h>
 #include <shogun/multiclass/MulticlassStrategy.h>
-#include <shogun/multiclass/ecoc/ECOCEncoder.h>
 #include <shogun/multiclass/ecoc/ECOCDecoder.h>
-
+#include <shogun/multiclass/ecoc/ECOCEncoder.h>
 
 namespace shogun
 {
@@ -104,6 +104,15 @@ namespace shogun
 		return result;
 	}
 
+	template <typename T, typename T2 = typename std::enable_if_t<
+	                          std::is_floating_point<T>::value>>
+	CKernel* kernel(SGMatrix<T> kernel_matrix)
+	{
+		CKernel* result = new CCustomKernel(kernel_matrix);
+		SG_REF(result);
+		return result;
+	}
+
 	CLabels* labels(CFile* file)
 	{
 		REQUIRE(file, "No file provided.\n");