text: # -*- coding: utf-8 -*-
  """
  @file
  @brief Implements class @see cl SkBaseClassifier.
  """
  from sklearn.metrics import accuracy_score
  from .sklearn_base_learner import SkBaseLearner
  
  
  class SkBaseClassifier(SkBaseLearner):
      """
      Defines a custom classifier.
      """
  
      def __init__(self, **kwargs):
          """
          constructor
          """
          SkBaseLearner.__init__(self, **kwargs)
  
      def score(self, X, y=None, sample_weight=None):
          """
          Returns the mean accuracy on the given test data and labels.
  
          @param      X               Training data, numpy array or sparse matrix of shape [n_samples,n_features]
          @param      y               Target values, numpy array of shape [n_samples, n_targets] (optional)
          @param      sample_weight   Weight values, numpy array of shape [n_samples, n_targets] (optional)
          @return                     score : float, Mean accuracy of self.predict(X) wrt. y.
          """
          return accuracy_score(y, self.predict(X), sample_weight=sample_weight)
  
      def predict_proba(self, X):
          """
          Returns probability estimates for the test data X.
  
          @param      X       Training data, numpy array or sparse matrix of shape [n_samples,n_features]
          @return             array, shape = (n_samples,.), Returns predicted values.
          """
          raise NotImplementedError()
  