assert np.all(P <= 1), ("All probabilities should be less " "or then equal to one") else: n_neighbors = min(n_samples - 1, int(3. * self.perplexity + 1)) if self.verbose: print("[t-SNE] Computing {} nearest neighbors...".format (n_neighbors)) # Find the nearest neighbor...
equivalent high-dimensional plots are much less intuitive. To aid visualization of the structure of a dataset, the dimension must be reduced in some way.
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assert np.all(P <= 1), ("All probabilities should be less " "or then equal to one") else: n_neighbors = min(n_samples - 1, int(3. * self.perplexity + 1)) if self.verbose: print("[t-SNE] Computing {} nearest neighbors...".format (n_neighbors)) # Find the nearest neighbor...
samples. For more tips see Laurens van der Maaten's FAQ [2]. Read more in the :ref:`User Guide <t_sne>`. Parameters --- n_components : int, optional (default: 2) Dimension of the embedded space. perplexity : float, optional (default: 30) The perplexity...