def fit(self, X, y=None, input_type='data'):
        X = self._validate_input(X, input_type)
        self.fit_geometry(X, input_type)
        random_state = check_random_state(self.random_state)
        self.embedding_, self.error_ = locally_linear_embedding(self.geom_,
                                                                n_components=self.n_components,
                                                                eigen_solver=self.eigen_solver,
                                                                tol=self.tol,
                                                                random_state=self.random_state,
                                                                reg=self.reg,
                                                                max_iter=self.max_iter)
        return self
Fit the model from data in X.
dataset/ETHPy150Open mmp2/megaman/megaman/embedding/locally_linear.py/LocallyLinearEmbedding.fit