class_docstr: Compatibility layer from River to scikit-learn for classification.
  
  Parameters
  ----------
  river_estimator
class_docstr_tok: ["Compatibility","layer","from","River","to","scikit-learn","for","classification",".","Parameters","--","--","--","--","--","river_estimator"]
docstr: Fits incrementally on a portion of a dataset.
  
  Parameters
  ----------
  X
      array-like of shape (n_samples, n_features).
  y
      array-like of shape n_samples.
  classes
      Classes across all calls to partial_fit. This argument is required for the first call
      to partial_fit and can be omitted in the subsequent calls. Note that y doesn't need to
      contain all labels in `classes`.
  
  Returns
  -------
  self
docstr_tok: ["Fits","incrementally","on","a","portion","of","a","dataset",".","Parameters","--","--","--","--","--","X","array-like","of","shape","(","n_samples",",","n_features",")",".","y","array-like","of","shape","n_samples",".","classes","Classes","across","all","calls","to","partial_fit",".","This","argument","is","required","for","the","first","call","to","partial_fit","and","can","be","omitted","in","the","subsequent","calls",".","Note","that","y","does","n't","need","to","contain","all","labels","in","`","classes","`",".","Returns","--","--","--","-","self"]
code: def partial_fit(self, X, y, classes=None):
      """Fits incrementally on a portion of a dataset.
  
      Parameters
      ----------
      X
          array-like of shape (n_samples, n_features).
      y
          array-like of shape n_samples.
      classes
          Classes across all calls to partial_fit. This argument is required for the first call
          to partial_fit and can be omitted in the subsequent calls. Note that y doesn't need to
          contain all labels in `classes`.
  
      Returns
      -------
      self
  
      """
  
      # Fit with one pass of the dataset portion
      return self._partial_fit(X, y, classes)
  
imports: from __future__ import annotations
  import copy
  import typing
  import numpy
  from sklearn import base
  from sklearn import pipeline, preprocessing, utils
  from river import base, compose, stream
label_desc: Use image node_id 5 for calling the River2SKLClassifier obj's underlying member method code with example usage: obj.partial_fit(X, y, classes) and returns: self