Python SubGradientSVM示例

示例#1

文件： classifier_subgradientsvm_modular.py 项目： Anshul-Bansal/gsoc

def classifier_subgradientsvm_modular(fm_train_real, fm_test_real, label_train_twoclass, C, epsilon, max_train_time):

    from shogun.Features import RealFeatures, SparseRealFeatures, Labels
    from shogun.Classifier import SubGradientSVM

    realfeat = RealFeatures(fm_train_real)
    feats_train = SparseRealFeatures()
    feats_train.obtain_from_simple(realfeat)
    realfeat = RealFeatures(fm_test_real)
    feats_test = SparseRealFeatures()
    feats_test.obtain_from_simple(realfeat)

    labels = Labels(label_train_twoclass)

    svm = SubGradientSVM(C, feats_train, labels)
    svm.set_epsilon(epsilon)
    svm.set_max_train_time(max_train_time)
    svm.train()

    svm.set_features(feats_test)
    labels = svm.apply().get_labels()

    return labels, svm

示例#2

def classifier_subgradientsvm_modular(fm_train_real, fm_test_real,
                                      label_train_twoclass, C, epsilon,
                                      max_train_time):

    from shogun.Features import RealFeatures, SparseRealFeatures, Labels
    from shogun.Classifier import SubGradientSVM

    realfeat = RealFeatures(fm_train_real)
    feats_train = SparseRealFeatures()
    feats_train.obtain_from_simple(realfeat)
    realfeat = RealFeatures(fm_test_real)
    feats_test = SparseRealFeatures()
    feats_test.obtain_from_simple(realfeat)

    labels = Labels(label_train_twoclass)

    svm = SubGradientSVM(C, feats_train, labels)
    svm.set_epsilon(epsilon)
    svm.set_max_train_time(max_train_time)
    svm.train()

    svm.set_features(feats_test)
    labels = svm.apply().get_labels()

    return labels, svm

示例#3

文件： classifier_subgradientsvm_modular.py 项目： polyactis/test

def subgradient_svm ():
	print 'SubGradientSVM'

	from shogun.Features import RealFeatures, SparseRealFeatures, Labels
	from shogun.Classifier import SubGradientSVM

	realfeat=RealFeatures(fm_train_real)
	feats_train=SparseRealFeatures()
	feats_train.obtain_from_simple(realfeat)
	realfeat=RealFeatures(fm_test_real)
	feats_test=SparseRealFeatures()
	feats_test.obtain_from_simple(realfeat)

	C=0.9
	epsilon=1e-3
	num_threads=1
	max_train_time=1.
	labels=Labels(label_train_twoclass)

	svm=SubGradientSVM(C, feats_train, labels)
	svm.set_epsilon(epsilon)
	svm.parallel.set_num_threads(num_threads)
	svm.set_bias_enabled(False)
	svm.set_max_train_time(max_train_time)
	svm.train()

	svm.set_features(feats_test)
	svm.classify().get_labels()