class_docstr: Base class for SparsePCA and MiniBatchSparsePCA
class_docstr_tok: ["Base","class","for","SparsePCA","and","MiniBatchSparsePCA"]
code: def _more_tags(self):
      return {
          "preserves_dtype": [np.float64, np.float32],
      }
  
imports: from numbers import Integral, Real
  import numpy
  from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
  from ..linear_model import ridge_regression
  from ..utils import check_random_state
  from ..utils._param_validation import Hidden, Interval, StrOptions
  from ..utils.extmath import svd_flip
  from ..utils.validation import check_array, check_is_fitted
  from ._dict_learning import MiniBatchDictionaryLearning, dict_learning
label_desc: Use image node_id 6 for calling the _BaseSparsePCA obj's underlying member method code with example usage: obj._more_tags() and returns: dict