from collections import Counter

import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split

UpperCamelCase  							=						datasets.load_iris()

UpperCamelCase  							=						np.array(data['''data'''])
UpperCamelCase  							=						np.array(data['''target'''])
UpperCamelCase  							=						data['''target_names''']

UpperCamelCase							,		UpperCamelCase							,		UpperCamelCase							,		UpperCamelCase  							=						train_test_split(X, y)

def 			lowercase_				(			_lowerCamelCase							:       str		,	_lowerCamelCase							:       Optional[Any]):
    return np.linalg.norm(np.array(_lowerCamelCase) - np.array(_lowerCamelCase))

def 			lowercase_				(			_lowerCamelCase							:       Optional[Any]		,	_lowerCamelCase							:       Optional[Any]		,	_lowerCamelCase							:       Optional[int]		,	_lowerCamelCase							:       Tuple		,	_lowerCamelCase							:       Any=5):
    lowercase__ :   int    					=				zip(_lowerCamelCase		,	_lowerCamelCase)
    # List of distances of all points from the point to be classified
    lowercase__ :   str    					=				[]
    for data_point in data:
        lowercase__ :   str    					=				euclidean_distance(data_point[0]		,	_lowerCamelCase)
        distances.append((distance, data_point[1]))
    # Choosing 'k' points with the least distances.
    lowercase__ :   Dict    					=				[i[1] for i in sorted(_lowerCamelCase)[:k]]
    # Most commonly occurring class among them
    # is the class into which the point is classified
    lowercase__ :   Tuple    					=				Counter(_lowerCamelCase).most_common(1)[0][0]
    return classes[result]


if __name__ == "__main__":
      print(classifier(X_train, y_train, classes, [4.4, 3.1, 1.3, 1.4]))








def     a(      A       :    list       )		->       list:
					"""simple docstring"""





					if any(not isinstance(A ,     A       ) or x < 0 for x in sequence       ):
										raise TypeError("Sequence must be list of non-negative integers"       )
					for _ in range(len(A       )       ):
										for i, (rod_upper, rod_lower) in enumerate(zip(A ,     sequence[1:]       )       ):
															if rod_upper > rod_lower:
																				sequence[i] -= rod_upper - rod_lower
																				sequence[i + 1] += rod_upper - rod_lower
					return sequence


if __name__ == "__main__":
				assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
				assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]
