def kernel_combined_modular(fm_train_real=traindat,fm_test_real=testdat,fm_train_dna=traindna,fm_test_dna=testdna ): from shogun.Kernel import CombinedKernel, GaussianKernel, FixedDegreeStringKernel, LocalAlignmentStringKernel from shogun.Features import RealFeatures, StringCharFeatures, CombinedFeatures, DNA kernel=CombinedKernel() feats_train=CombinedFeatures() feats_test=CombinedFeatures() subkfeats_train=RealFeatures(fm_train_real) subkfeats_test=RealFeatures(fm_test_real) subkernel=GaussianKernel(10, 1.1) feats_train.append_feature_obj(subkfeats_train) feats_test.append_feature_obj(subkfeats_test) kernel.append_kernel(subkernel) subkfeats_train=StringCharFeatures(fm_train_dna, DNA) subkfeats_test=StringCharFeatures(fm_test_dna, DNA) degree=3 subkernel=FixedDegreeStringKernel(10, degree) feats_train.append_feature_obj(subkfeats_train) feats_test.append_feature_obj(subkfeats_test) kernel.append_kernel(subkernel) subkfeats_train=StringCharFeatures(fm_train_dna, DNA) subkfeats_test=StringCharFeatures(fm_test_dna, DNA) subkernel=LocalAlignmentStringKernel(10) feats_train.append_feature_obj(subkfeats_train) feats_test.append_feature_obj(subkfeats_test) kernel.append_kernel(subkernel) kernel.init(feats_train, feats_train) km_train=kernel.get_kernel_matrix() kernel.init(feats_train, feats_test) km_test=kernel.get_kernel_matrix() return km_train,km_test,kernel
def kernel_combined_modular(fm_train_real=traindat, fm_test_real=testdat, fm_train_dna=traindna, fm_test_dna=testdna): from shogun.Kernel import CombinedKernel, GaussianKernel, FixedDegreeStringKernel, LocalAlignmentStringKernel from shogun.Features import RealFeatures, StringCharFeatures, CombinedFeatures, DNA kernel = CombinedKernel() feats_train = CombinedFeatures() feats_test = CombinedFeatures() subkfeats_train = RealFeatures(fm_train_real) subkfeats_test = RealFeatures(fm_test_real) subkernel = GaussianKernel(10, 1.1) feats_train.append_feature_obj(subkfeats_train) feats_test.append_feature_obj(subkfeats_test) kernel.append_kernel(subkernel) subkfeats_train = StringCharFeatures(fm_train_dna, DNA) subkfeats_test = StringCharFeatures(fm_test_dna, DNA) degree = 3 subkernel = FixedDegreeStringKernel(10, degree) feats_train.append_feature_obj(subkfeats_train) feats_test.append_feature_obj(subkfeats_test) kernel.append_kernel(subkernel) subkfeats_train = StringCharFeatures(fm_train_dna, DNA) subkfeats_test = StringCharFeatures(fm_test_dna, DNA) subkernel = LocalAlignmentStringKernel(10) feats_train.append_feature_obj(subkfeats_train) feats_test.append_feature_obj(subkfeats_test) kernel.append_kernel(subkernel) kernel.init(feats_train, feats_train) km_train = kernel.get_kernel_matrix() kernel.init(feats_train, feats_test) km_test = kernel.get_kernel_matrix() return km_train, km_test, kernel
def kernel_combined_custom_poly_modular(fm_train_real=traindat, fm_test_real=testdat, fm_label_twoclass=label_traindat): from shogun.Features import CombinedFeatures, RealFeatures, Labels from shogun.Kernel import CombinedKernel, PolyKernel, CustomKernel from shogun.Classifier import LibSVM kernel = CombinedKernel() feats_train = CombinedFeatures() tfeats = RealFeatures(fm_train_real) tkernel = PolyKernel(10, 3) tkernel.init(tfeats, tfeats) K = tkernel.get_kernel_matrix() kernel.append_kernel(CustomKernel(K)) subkfeats_train = RealFeatures(fm_train_real) feats_train.append_feature_obj(subkfeats_train) subkernel = PolyKernel(10, 2) kernel.append_kernel(subkernel) kernel.init(feats_train, feats_train) labels = Labels(fm_label_twoclass) svm = LibSVM(1.0, kernel, labels) svm.train() kernel = CombinedKernel() feats_pred = CombinedFeatures() pfeats = RealFeatures(fm_test_real) tkernel = PolyKernel(10, 3) tkernel.init(tfeats, pfeats) K = tkernel.get_kernel_matrix() kernel.append_kernel(CustomKernel(K)) subkfeats_test = RealFeatures(fm_test_real) feats_pred.append_feature_obj(subkfeats_test) subkernel = PolyKernel(10, 2) kernel.append_kernel(subkernel) kernel.init(feats_train, feats_pred) svm.set_kernel(kernel) svm.classify() km_train = kernel.get_kernel_matrix() return km_train, kernel
def kernel_combined_custom_poly_modular(fm_train_real = traindat,fm_test_real = testdat,fm_label_twoclass=label_traindat): from shogun.Features import CombinedFeatures, RealFeatures, BinaryLabels from shogun.Kernel import CombinedKernel, PolyKernel, CustomKernel from shogun.Classifier import LibSVM kernel = CombinedKernel() feats_train = CombinedFeatures() tfeats = RealFeatures(fm_train_real) tkernel = PolyKernel(10,3) tkernel.init(tfeats, tfeats) K = tkernel.get_kernel_matrix() kernel.append_kernel(CustomKernel(K)) subkfeats_train = RealFeatures(fm_train_real) feats_train.append_feature_obj(subkfeats_train) subkernel = PolyKernel(10,2) kernel.append_kernel(subkernel) kernel.init(feats_train, feats_train) labels = BinaryLabels(fm_label_twoclass) svm = LibSVM(1.0, kernel, labels) svm.train() kernel = CombinedKernel() feats_pred = CombinedFeatures() pfeats = RealFeatures(fm_test_real) tkernel = PolyKernel(10,3) tkernel.init(tfeats, pfeats) K = tkernel.get_kernel_matrix() kernel.append_kernel(CustomKernel(K)) subkfeats_test = RealFeatures(fm_test_real) feats_pred.append_feature_obj(subkfeats_test) subkernel = PolyKernel(10, 2) kernel.append_kernel(subkernel) kernel.init(feats_train, feats_pred) svm.set_kernel(kernel) svm.apply() km_train=kernel.get_kernel_matrix() return km_train,kernel