




import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor




def    SCREAMING_SNAKE_CASE      (			__UpperCamelCase     :		List[Any] )    ->				Optional[int]:
    return (data["data"], data["target"])




def    SCREAMING_SNAKE_CASE      (			__UpperCamelCase     :		List[str]			,	__UpperCamelCase     :		str			,	__UpperCamelCase     :		str )    ->				List[str]:
    UpperCAmelCase_									=	XGBRegressor(verbosity=0			,	random_state=42 )
    xgb.fit(lowercase__			,	lowercase__ )
    # Predict target for test data
    UpperCAmelCase_									=	xgb.predict(lowercase__ )
    UpperCAmelCase_									=	predictions.reshape(len(lowercase__ )			,	1 )
    return predictions




def    SCREAMING_SNAKE_CASE      (			)    ->				List[str]:
    UpperCAmelCase_									=	fetch_california_housing()
    UpperCAmelCase_					,				UpperCAmelCase_									=	data_handling(lowercase__ )
    UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_									=	train_test_split(
        lowercase__			,	lowercase__			,	test_size=0.25			,	random_state=1 )
    UpperCAmelCase_									=	xgboost(lowercase__			,	lowercase__			,	lowercase__ )
    # Error printing
    print(f'Mean Absolute Error : {mean_absolute_error(lowercase__			,	lowercase__ )}' )
    print(f'Mean Square Error  : {mean_squared_error(lowercase__			,	lowercase__ )}' )


if __name__ == "__main__":
 import doctest

 doctest.testmod(verbose=True)
 main()








from __future__ import annotations





def a(lowercase__      ,			lowercase__      ,			lowercase__      ,			lowercase__						):





	'''simple docstring'''
	if (direction == 1 and array[indexa] > array[indexa]) or (
	    direction == 0 and array[indexa] < array[indexa]
	):
		snake_case_		,							snake_case_   		=			array[indexa], array[indexa]





def a(lowercase__      ,			lowercase__      ,			lowercase__      ,			lowercase__						):





	'''simple docstring'''
	if length > 1:
		snake_case_   		=			int(length / 2						)
		for i in range(lowercase__      ,			low + middle						):
			comp_and_swap(lowercase__      ,			lowercase__      ,			i + middle      ,			lowercase__						)
		bitonic_merge(lowercase__      ,			lowercase__      ,			lowercase__      ,			lowercase__						)
		bitonic_merge(lowercase__      ,			low + middle      ,			lowercase__      ,			lowercase__						)





def a(lowercase__      ,			lowercase__      ,			lowercase__      ,			lowercase__						):





	'''simple docstring'''
	if length > 1:
		snake_case_   		=			int(length / 2						)
		bitonic_sort(lowercase__      ,			lowercase__      ,			lowercase__      ,			1						)
		bitonic_sort(lowercase__      ,			low + middle      ,			lowercase__      ,			0						)
		bitonic_merge(lowercase__      ,			lowercase__      ,			lowercase__      ,			lowercase__						)


if __name__ == "__main__":
		A									=  input('Enter numbers separated by a comma:\n').strip()
		A									=  [int(item.strip()) for item in user_input.split(',')]

		bitonic_sort(unsorted, 0, len(unsorted), 1)
		print('\nSorted array in ascending order is: ', end='')
		print(*unsorted, sep=', ')

		bitonic_merge(unsorted, 0, len(unsorted), 0)
		print('Sorted array in descending order is: ', end='')
		print(*unsorted, sep=', ')
