Python SVMSGDの例

コード例 #1

ファイル: classifier_svmsgd_modular.py プロジェクト: polyactis/test

def svmsgd ():
	print 'SVMSGD'

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

	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	
	num_threads=1
	num_iter=5
	labels=Labels(label_train_twoclass)

	svm=SVMSGD(C, feats_train, labels)
	svm.set_epochs(num_iter)
	#svm.io.set_loglevel(0)
	svm.train()
	
	
	svm.set_features(feats_test)
	labelPrediction = svm.classify().get_labels()
	print labelPrediction>0

コード例 #2

ファイル: classifier_svmsgd_modular.py プロジェクト: memimo/shogun-liblinear

def svmsgd ():
	print 'SVMSGD'

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

	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-5
	num_threads=1
	labels=Labels(label_train_twoclass)

	svm=SVMSGD(C, feats_train, labels)
	#svm.io.set_loglevel(0)
	svm.train()

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

コード例 #3

ファイル: classifier_svmsgd_modular.py プロジェクト: Anshul-Bansal/gsoc

def classifier_svmsgd_modular (fm_train_real=traindat,fm_test_real=testdat,label_train_twoclass=label_traindat,C=0.9,num_threads=1,num_iter=5):

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

	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=SVMSGD(C, feats_train, labels)
	svm.set_epochs(num_iter)
	#svm.io.set_loglevel(0)
	svm.train()

	svm.set_features(feats_test)
	svm.apply().get_labels()
	predictions = svm.apply()
	return predictions, svm, predictions.get_labels()