class_docstr: Base class for spectral biclustering.
class_docstr_tok: ["Base","class","for","spectral","biclustering","."]
docstr: Validate parameters depending on the input data.
docstr_tok: ["Validate","parameters","depending","on","the","input","data","."]
code: def _check_parameters(self, n_samples):
      """Validate parameters depending on the input data."""
  
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 2 for calling the BaseSpectral obj's underlying member method code with example usage: obj._check_parameters(n_samples) without return types