def predict_proba(self, X):
<EOL>check_is_fitted(self, ['<STR_LIT>'])<EOL>X = check_array(X)<EOL>return self.tree.query(X)[<NUM_LIT:0>].flatten()<EOL>
Returns the value of the nearest neighbor from the training set.

        Parameters
        ----------
         X : array-like or sparse matrix, shape (n_samples, n_features)
            The input samples. Internally, it will be converted to
            ``dtype=np.float32`` and if a sparse matrix is provided
            to a sparse ``csr_matrix``.

        Returns
        -------
        y : array, shape (n_samples,)