本文整理匯總了Python中shogun.Classifier.LibSVM.get_alphas方法的典型用法代碼示例。如果您正苦於以下問題：Python LibSVM.get_alphas方法的具體用法？Python LibSVM.get_alphas怎麽用？Python LibSVM.get_alphas使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類shogun.Classifier.LibSVM的用法示例。
在下文中一共展示了LibSVM.get_alphas方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: classifier_libsvm_modular
# 需要導入模塊: from shogun.Classifier import LibSVM [as 別名]
# 或者: from shogun.Classifier.LibSVM import get_alphas [as 別名]
def classifier_libsvm_modular (fm_train_real=traindat,fm_test_real=testdat,label_train_twoclass=label_traindat,width=2.1,C=1,epsilon=1e-5):
from shogun.Features import RealFeatures, Labels
from shogun.Kernel import GaussianKernel
from shogun.Classifier import LibSVM
feats_train=RealFeatures(fm_train_real)
feats_test=RealFeatures(fm_test_real)
kernel=GaussianKernel(feats_train, feats_train, width)
labels=Labels(label_train_twoclass)
svm=LibSVM(C, kernel, labels)
svm.set_epsilon(epsilon)
svm.train()
kernel.init(feats_train, feats_test)
labels = svm.apply().get_labels()
supportvectors = sv_idx=svm.get_support_vectors()
alphas=svm.get_alphas()
predictions = svm.apply()
return predictions, svm, predictions.get_labels()示例2: libsvm
# 需要導入模塊: from shogun.Classifier import LibSVM [as 別名]
# 或者: from shogun.Classifier.LibSVM import get_alphas [as 別名]
def libsvm ():
print 'LibSVM'
from shogun.Features import RealFeatures, Labels
from shogun.Kernel import GaussianKernel
from shogun.Classifier import LibSVM
feats_train=RealFeatures(fm_train_real)
feats_test=RealFeatures(fm_test_real)
width=2.1
kernel=GaussianKernel(feats_train, feats_train, width)
C=1
epsilon=1e-5
labels=Labels(label_train_twoclass)
svm=LibSVM(C, kernel, labels)
svm.set_epsilon(epsilon)
svm.train()
kernel.init(feats_train, feats_test)
svm.classify().get_labels()
sv_idx=svm.get_support_vectors()
alphas=svm.get_alphas()