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T-SNE with sparse matrix
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| from sklearn.neighbors import kneighbors_graph | |
| from sklearn.manifold import TSNE | |
| import numpy as np | |
| X = np.random.rand(100,10) | |
| distances = kneighbors_graph(X, n_neighbors=40, mode="distance", metric="cosine") | |
| X_embedded = TSNE(n_components=2, metric="precomputed").fit_transform(distances) | |
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