class_docstr: Wrap estimator which will not expose `sample_weight`.
  
  Parameters
  ----------
  est : estimator, default=None
      The estimator to wrap.
class_docstr_tok: ["Wrap","estimator","which","will","not","expose","`","sample_weight","`",".","Parameters","--","--","--","--","--","est",":","estimator",",","default=None","The","estimator","to","wrap","."]
code: def _more_tags(self):
      return {"_skip_test": True}
  
imports: import numpy
  from ..base import BaseEstimator, ClassifierMixin
  from ..utils._metadata_requests import RequestMethod
  from .metaestimators import available_if
  from .validation import _check_sample_weight, _num_samples, check_array, check_is_fitted
label_desc: Use image node_id 5 for calling the NoSampleWeightWrapper obj's underlying member method code with example usage: obj._more_tags() and returns: dict