Ejemplos de MulticlassLibSVM.load_serializable en Python

Ejemplo n.º 1

Archivo: predict_multiclass_svm.py Proyecto: 42MachineLearning/shogun

def main(classifier, testset, output):
	LOGGER.info("SVM Multiclass evaluation")

	svm = MulticlassLibSVM()
	serialized_classifier = SerializableHdf5File(classifier, 'r')
	with closing(serialized_classifier):
		svm.load_serializable(serialized_classifier)

	test_feats, test_labels = get_features_and_labels(LibSVMFile(testset))
	predicted_labels = svm.apply(test_feats)

	with open(output, 'w') as f:
		for cls in predicted_labels.get_labels():
			f.write("%s\n" % int(cls))

	LOGGER.info("Predicted labels saved in: '%s'" % output)

Ejemplo n.º 2

Archivo: predict_multiclass_svm.py Proyecto: manantomar/test

def main(classifier, testset, output):
    LOGGER.info("SVM Multiclass evaluation")

    svm = MulticlassLibSVM()
    serialized_classifier = SerializableHdf5File(classifier, 'r')
    with closing(serialized_classifier):
        svm.load_serializable(serialized_classifier)

    test_feats, test_labels = get_features_and_labels(LibSVMFile(testset))
    predicted_labels = svm.apply(test_feats)

    with open(output, 'w') as f:
        for cls in predicted_labels.get_labels():
            f.write("%s\n" % int(cls))

    LOGGER.info("Predicted labels saved in: '%s'" % output)