def preprocessor_laplacianeigenmaps_modular(data,k): from shogun.Features import RealFeatures from shogun.Preprocessor import LaplacianEigenmaps features = RealFeatures(data) preprocessor = LaplacianEigenmaps() preprocessor.set_target_dim(1) preprocessor.set_k(k) preprocessor.set_tau(2.0) preprocessor.apply_to_feature_matrix(features) return features
lisomap.set_landmark_number(500) lisomap.set_k(9) preprocs.append((lisomap,"K-LIsomap with k=%d, %d landmarks" % (lisomap.get_k(),lisomap.get_landmark_number()))) from shogun.Preprocessor import HessianLocallyLinearEmbedding hlle = HessianLocallyLinearEmbedding() hlle.set_k(6) preprocs.append((hlle,"Hessian LLE with k=%d" % (hlle.get_k()))) from shogun.Preprocessor import LocalTangentSpaceAlignment ltsa = LocalTangentSpaceAlignment() ltsa.set_k(6) preprocs.append((ltsa,"LTSA with k=%d" % (ltsa.get_k()))) from shogun.Preprocessor import LaplacianEigenmaps le = LaplacianEigenmaps() le.set_k(15) le.set_tau(25.0) preprocs.append((le,"Laplacian Eigenmaps with k=%d, tau=%d" % (le.get_k(),le.get_tau()))) import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D fig = plt.figure() swiss_roll_fig = fig.add_subplot(3,3,1,projection='3d') swiss_roll_fig.scatter(X[0], X[1], X[2], s=10, c=tt, cmap=plt.cm.Spectral) plt.subplots_adjust(hspace=0.4) from shogun.Features import RealFeatures for (i, (preproc, label)) in enumerate(preprocs):
lisomap.set_k(9) preprocs.append((lisomap, "K-LIsomap with k=%d, %d landmarks" % (lisomap.get_k(), lisomap.get_landmark_number()))) from shogun.Preprocessor import HessianLocallyLinearEmbedding hlle = HessianLocallyLinearEmbedding() hlle.set_k(6) preprocs.append((hlle, "Hessian LLE with k=%d" % (hlle.get_k()))) from shogun.Preprocessor import LocalTangentSpaceAlignment ltsa = LocalTangentSpaceAlignment() ltsa.set_k(6) preprocs.append((ltsa, "LTSA with k=%d" % (ltsa.get_k()))) from shogun.Preprocessor import LaplacianEigenmaps le = LaplacianEigenmaps() le.set_k(15) le.set_tau(25.0) preprocs.append( (le, "Laplacian Eigenmaps with k=%d, tau=%d" % (le.get_k(), le.get_tau()))) import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D fig = plt.figure() swiss_roll_fig = fig.add_subplot(3, 3, 1, projection='3d') swiss_roll_fig.scatter(X[0], X[1], X[2], s=10, c=tt, cmap=plt.cm.Spectral) plt.subplots_adjust(hspace=0.4) from shogun.Features import RealFeatures