class_docstr: Estimator mixin
  
  Mixin class to build an estimator from a :mod:`mlens.parallel` backend
  class. The backend class should be set as the ``_backend`` attribute
  of the estimator during a ``fit`` call via a ``_build`` method. E.g::
  
      Foo(EstimatorMixin, Learner):
  
          def __init__(self, ...):
  
              self._backend = None
  
          def _build(self):
              self._backend = Learner(...)
  
  It is recommended to combine :class:`EstimatorMixin` with
  `parallel.base.ParamMixin`.
docstr: Predict
  
  Predict using full-fold estimator (fitted on all data).
  
  Parameters
  ----------
  X: array of size [n_samples, n_features]
      input data
  
  proba: bool, optional
      whether to predict class probabilities
  
  Returns
  -------
  P: array of size [n_samples, n_prediction_features]
      prediction with full-fold estimator.
docstr_tok: ["Predict","Predict","using","full-fold","estimator","(","fitted","on","all","data",")",".","Parameters","--","--","--","--","--","X",":","array","of","size","[","n_samples",",","n_features","]","input","data","proba",":","bool",",","optional","whether","to","predict","class","probabilities","Returns","--","--","--","-","P",":","array","of","size","[","n_samples",",","n_prediction_features","]","prediction","with","full-fold","estimator","."]
code: def predict(self, X, proba=False):
      """Predict
  
      Predict using full-fold estimator (fitted on all data).
  
      Parameters
      ----------
      X: array of size [n_samples, n_features]
          input data
  
      proba: bool, optional
          whether to predict class probabilities
  
      Returns
      -------
      P: array of size [n_samples, n_prediction_features]
          prediction with full-fold estimator.
      """
      if hasattr(self, "__fitted__"):
          if not self.__fitted__:
              raise NotFittedError(
                  "Instance not fitted (with current params)."
              )
  
      return run(
          get_backend(self),
          "predict",
          X,
          proba=proba,
          return_preds=True,
      )
  
file_path: mlens/mlens/parallel/wrapper.py
imports: from ..None import config
  from .base import BaseParallel, OutputMixin
  from .backend import ParallelProcessing
  from ..utils.exceptions import ParallelProcessingError, NotFittedError
label_desc: Use image node_id 3 for calling the EstimatorMixin obj's underlying member method code with example usage: obj.predict(X, proba) and returns: run