





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__  (       _lowercase     : dict			)   ->							tuple:




		'''simple docstring'''
		return (data["data"], data["target"])


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : np.ndarray   ,    _lowercase     : np.ndarray   ,    _lowercase     : np.ndarray			)   ->							np.ndarray:




		'''simple docstring'''
		lowercase__					:      List[str]      =		XGBRegressor(verbosity=0   ,    random_state=42			)
		xgb.fit(_lowercase   ,    _lowercase			)
		# Predict target for test data
		lowercase__					:      Union[str, Any]      =		xgb.predict(_lowercase			)
		lowercase__					:      Tuple      =		predictions.reshape(len(_lowercase			)   ,    1			)
		return predictions


def       SCREAMING_SNAKE_CASE__  (       )   ->							None:




		'''simple docstring'''
		lowercase__					:      List[str]      =		fetch_california_housing()
		lowercase__   ,				lowercase__					:      Optional[int]      =		data_handling(_lowercase			)
		lowercase__   ,				lowercase__   ,				lowercase__   ,				lowercase__					:      Optional[Any]      =		train_test_split(
		    _lowercase   ,    _lowercase   ,    test_size=0.25   ,    random_state=1			)
		lowercase__					:      Any      =		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()









import enum
import shutil
import sys


__UpperCamelCase,	__UpperCamelCase:	Optional[int] = shutil.get_terminal_size()

__UpperCamelCase:	Optional[Any] = {"""UP""": """A""", """DOWN""": """B""", """RIGHT""": """C""", """LEFT""": """D"""}


class       __lowerCAmelCase					(       enum.Enum      ):


	'''simple docstring'''





	_A													=				0
	_A													=				1


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : List[Any]   ,    _lowercase     : Union[str, Any]=""			)   ->							int:




		'''simple docstring'''
		sys.stdout.write(str(_lowercase			) + end			)
		sys.stdout.flush()


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : Optional[Any]   ,    _lowercase     : Union[str, Any]   ,    _lowercase     : Optional[int]=""			)   ->							str:




		'''simple docstring'''
		forceWrite(f"""\u001b[{color}m{content}\u001b[0m"""   ,    _lowercase			)


def       SCREAMING_SNAKE_CASE__  (       )   ->							int:




		'''simple docstring'''
		forceWrite('\r'			)


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : int   ,    _lowercase     : str			)   ->							List[Any]:




		'''simple docstring'''
		forceWrite(f"""\033[{num_lines}{CURSOR_TO_CHAR[direction.upper()]}"""			)


def       SCREAMING_SNAKE_CASE__  (       )   ->							Dict:




		'''simple docstring'''
		forceWrite(' ' * TERMINAL_WIDTH			)
		reset_cursor()





def       SCREAMING_SNAKE_CASE__  (       )   ->							List[str]:




		'''simple docstring'''
		reset_cursor()
		forceWrite('-' * TERMINAL_WIDTH			)


