title: Latest XGboost and Sklearn giving error
body: <pre><code>xgb=XGBClassifier(objective="binary:logistic", n_estimators=100, random_state=42, eval_metric=["auc"])
  </code></pre>
  
  <h2>    xgb.fit(X_train, y_train)</h2>
  
  <p>KeyError                                  Traceback (most recent call last)
  ~/.pyenv/versions/3.7.4/envs/py3env/lib/python3.7/site-packages/IPython/core/formatters.py in <strong>call</strong>(self, obj, include, exclude)
      968 
      969             if method is not None:
  --> 970                 return method(include=include, exclude=exclude)
      971             return None
      972         else:</p>
  
  <p>~/.pyenv/versions/3.7.4/envs/py3env/lib/python3.7/site-packages/sklearn/base.py in _repr_mimebundle_(self, **kwargs)
      461 
      462     def get_indices(self, i):
  --> 463         """Row and column indices of the i'th bicluster.
      464 
      465         Only works if <code>rows_</code> and <code>columns_</code> attributes exist.</p>
  
  <p>~/.pyenv/versions/3.7.4/envs/py3env/lib/python3.7/site-packages/sklearn/base.py in <strong>repr</strong>(self, N_CHAR_MAX)
      277                 right_lim = re.match(regex, repr_[::-1]).end()
      278 
  --> 279             ellipsis = '...'
      280             if left_lim + len(ellipsis) &lt; len(repr_) - right_lim:
      281                 # Only add ellipsis if it results in a shorter repr</p>
  
  <p>~/.pyenv/versions/3.7.4/lib/python3.7/pprint.py in pformat(self, object)
      142     def pformat(self, object):
      143         sio = _StringIO()
  --> 144         self._format(object, sio, 0, 0, {}, 0)
      145         return sio.getvalue()
      146 </p>
  
  <p>~/.pyenv/versions/3.7.4/lib/python3.7/pprint.py in _format(self, object, stream, indent, allowance, context, level)
      159             self._readable = False
      160             return
  --> 161         rep = self._repr(object, context, level)
      162         max_width = self._width - indent - allowance
      163         if len(rep) > max_width:</p>
  
  <p>~/.pyenv/versions/3.7.4/lib/python3.7/pprint.py in _repr(self, object, context, level)
      391     def _repr(self, object, context, level):
      392         repr, readable, recursive = self.format(object, context.copy(),
  --> 393                                                 self._depth, level)
      394         if not readable:
      395             self._readable = False</p>
  
  <p>~/.pyenv/versions/3.7.4/envs/py3env/lib/python3.7/site-packages/sklearn/utils/_pprint.py in format(self, object, context, maxlevels, level)
      168     def format(self, object, context, maxlevels, level):
      169         return _safe_repr(object, context, maxlevels, level,
  --> 170                           changed_only=self._changed_only)
      171 
      172     def _pprint_estimator(self, object, stream, indent, allowance, context,</p>
  
  <p>~/.pyenv/versions/3.7.4/envs/py3env/lib/python3.7/site-packages/sklearn/utils/_pprint.py in _safe_repr(object, context, maxlevels, level, changed_only)
      412         if changed_only:
      413             params = _changed_params(object)
  --> 414         else:
      415             params = object.get_params(deep=False)
      416         components = []</p>
  
  <p>~/.pyenv/versions/3.7.4/envs/py3env/lib/python3.7/site-packages/sklearn/utils/_pprint.py in _changed_params(estimator)
       96     init_params = {name: param.default for name, param in init_params.items()}
       97     for k, v in params.items():
  ---> 98         if (repr(v) != repr(init_params[k]) and
       99                 not (is_scalar_nan(init_params[k]) and is_scalar_nan(v))):
      100             filtered_params[k] = v</p>
  
  <p>KeyError: 'base_score'</p>
  
  <p>Name: xgboost
  Version: 1.0.2</p>
  
  <p>scikit-learn-0.23.0</p>
  
  <p>pyhton 3</p>