text: #!/usr/bin/python
  #-*- coding: utf-8 -*-
  
  from src.Classifiers import Classifier
  from sklearn.linear_model import SGDClassifier
  
  
  class Perceptron(Classifier):
      def __init__(self, **kwargs):
          super().__init__()
          self._model = SGDClassifier(**kwargs)
  
      def fit(self, X, Y):
          """
          Training model with data provided.
          Parameters
          ==========
          X: Pandas DataFrame. Attribute Values
          Y: Pandas Series.    Object labels.
  
          Returns
          =======
          void.
          """
          X = X.values
          Y = Y.values
  
          self._model.fit(X=X, y=Y)
  
      def predict(self, X):
          """
          Returns prediction label for X.
  
          Parameters
          ==========
          X: Pandas DataFrame -> Data to predict value
  
          Returns
          =======
          Prediction labels: array like of size (nsamples, [n_features])
          """
  
          pred = self._model.predict(X)
  
          return pred
  
  