input: 
  import pandas as pd
  
  #importing the dataset 
  dataset = pd.read_csv('data.csv')
  
  #splitting the dataset into features and labels 
  X = dataset.iloc[:, :-1].values 
  y = dataset.iloc[:, 3].values
  
  #importing DecisionTreeClassifier 
  from sklearn.tree import DecisionTreeClassifier
  
  classifier = DecisionTreeClassifier(criterion = 'entropy')
  
  #fitting the classifier to the dataset
  classifier.fit(X,y)
  
  """Write a function that predicts the fourth feature using the decision tree classifier.
  
  >>> classifier.predict([[1, 2, 3]])
  [0]
  >>> classifier.predict([[4, 5, 6]])
  [1]
  """
  
output:     
  def predict_fourth_feature(input_data):
      return classifier.predict([input_data])[0]
  