示例#1
0
def converter_isomap_modular(data_fname):
    from modshogun import RealFeatures, CSVFile
    from modshogun import Isomap

    features = RealFeatures(CSVFile(data))

    converter = Isomap()
    converter.set_k(20)
    converter.set_target_dim(1)
    converter.apply(features)

    return features
def converter_isomap_modular(data_fname):
    try:
        from modshogun import RealFeatures, Isomap, CSVFile

        features = RealFeatures(CSVFile(data))

        converter = Isomap()
        converter.set_k(20)
        converter.set_target_dim(1)
        converter.apply(features)

        return features
    except ImportError:
        print('No Eigen3 available')
def converter_isomap_modular (data_fname):
	from modshogun import RealFeatures, CSVFile
	from modshogun import Isomap
		
	features = RealFeatures(CSVFile(data))

	converter = Isomap()
	converter.set_k(20)
	converter.set_target_dim(1)
	converter.apply(features)

	return features
def converter_isomap_modular (data_fname):
	try:
		from modshogun import RealFeatures, Isomap, CSVFile
		
		features = RealFeatures(CSVFile(data))
			
		converter = Isomap()
		converter.set_k(20)
		converter.set_target_dim(1)
		converter.apply(features)

		return features
	except ImportError:
		print('No Eigen3 available')
示例#5
0
# Compute a second SPE embedding with local strategy
converter.set_strategy(SPE_LOCAL)
converter.set_k(12)
embedding = converter.embed(features)

X = embedding.get_feature_matrix()

fig.add_subplot(2, 2, 3)

pylab.plot(X[0, y1], X[1, y1], 'ro')
pylab.plot(X[0, y2], X[1, y2], 'go')

pylab.title('SPE with local strategy')

# Compute Isomap embedding (for comparison)
converter = Isomap()
converter.set_target_dim(2)
converter.set_k(6)

embedding = converter.embed(features)

X = embedding.get_feature_matrix()

fig.add_subplot(2, 2, 4)

pylab.plot(X[0, y1], X[1, y1], 'ro')
pylab.plot(X[0, y2], X[1, y2], 'go')

pylab.title('Isomap')

pylab.connect('key_press_event', util.quit)