def main(): # X = np.arange(9).reshape(9,1).astype(np.float64) X = np.array(dg.get_swiss_roll_dataset(5000), np.float64) print("The input data:") print(X) # for test only Y, error = locally_linear_embedding(X, 5, 2) print("The output data:") print(Y) # for test only print(error) # for test only
hd_dataset = dg.get_hd_dataset(5000) reduced_hd = eval.pca_dim_reduction(hd_dataset, 3) ploter.plot3D(reduced_hd) broken_swiss_roll_dataset = dg.get_broken_swiss_roll_dataset(5000) ploter.plot3D(broken_swiss_roll_dataset) reduced_broken_swiss = eval.pca_dim_reduction(broken_swiss_roll_dataset, 2) ploter.plot2D(reduced_broken_swiss) broken_helix_dataset = dg.get_helix_dataset(5000) ploter.plot3D(broken_helix_dataset) reduced_helix = eval.pca_dim_reduction(broken_helix_dataset, 2) ploter.plot2D(reduced_helix) swiss_roll_dataset = dg.get_swiss_roll_dataset(5000) ploter.plot3D(swiss_roll_dataset) reduced_swiss = eval.pca_dim_reduction(swiss_roll_dataset, 2) ploter.plot2D(reduced_swiss) twin_peaks_dataset = dg.get_twin_peaks(5000) ploter.plot3D(twin_peaks_dataset) reduced_twin_peaks = eval.pca_dim_reduction(twin_peaks_dataset, 2) ploter.plot2D(reduced_twin_peaks) # ***********************************scripts to evaluate Trust # Swiss roll import Dataset_Generator as dg import Evaluation as eval