code: 
  
  
  
  from sklearn.datasets import load_iris
  from sklearn.model_selection import train_test_split
  from sklearn.neighbors import KNeighborsClassifier
  
  # Load iris file
  lowerCAmelCase__	:  Dict 		=load_iris()
  iris.keys()
  
  
  print(F'''Target names: \n {iris.target_names} ''')
  print(F'''\n Features: \n {iris.feature_names}''')
  
  # Train set e Test set
  lowerCAmelCase__	:  Dict 		=train_test_split(
      iris['''data'''], iris['''target'''], random_state=4
  )
  
  # KNN
  
  lowerCAmelCase__	:  int 		=KNeighborsClassifier(n_neighbors=1)
  knn.fit(X_train, y_train)
  
  # new array to test
  lowerCAmelCase__	:  Dict 		=[[1, 2, 1, 4], [2, 3, 4, 5]]
  
  lowerCAmelCase__	:  Tuple 		=knn.predict(X_new)
  
  print(
      F'''\nNew array: \n {X_new}\n\nTarget Names Prediction: \n'''
      F''' {iris['target_names'][prediction]}'''
  )
style_context: 
  
  
  
  def 			__lowercase     (				a__     )       ->				int:
  							return int(a__     ) if x - int(a__     ) <= 0 else int(a__     ) + 1
  
  
  if __name__ == "__main__":
  			import doctest
  
  			doctest.testmod()
  
  
  
  
  
  
  