class_docstr: Base class for spectral biclustering.
code: def __init__(
      self,
      n_clusters=3,
      svd_method="randomized",
      n_svd_vecs=None,
      mini_batch=False,
      init="k-means++",
      n_init=10,
      random_state=None,
  ):
      self.n_clusters = n_clusters
      self.svd_method = svd_method
      self.n_svd_vecs = n_svd_vecs
      self.mini_batch = mini_batch
      self.init = init
      self.n_init = n_init
      self.random_state = random_state
  
imports: from abc import ABCMeta, abstractmethod
  from numbers import Integral
  import numpy
  from scipy.linalg import norm
  from scipy.sparse import dia_matrix, issparse
  from scipy.sparse.linalg import eigsh, svds
  from ..base import BaseEstimator, BiclusterMixin, _fit_context
  from ..utils import check_random_state, check_scalar
  from ..utils._param_validation import Interval, StrOptions
  from ..utils.extmath import make_nonnegative, randomized_svd, safe_sparse_dot
  from ..utils.validation import assert_all_finite
  from ._kmeans import KMeans, MiniBatchKMeans
label_desc: Use image node_id 1 to create a new BaseSpectral object from inherited base classes: BiclusterMixin, BaseEstimator with example: obj = BaseSpectral(n_clusters, svd_method, n_svd_vecs, mini_batch, init, n_init, random_state)