

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 		UpperCamelCase      (lowercase_:				int      )  ->   str:
	return (data["data"], data["target"])

def 		UpperCamelCase      (lowercase_:				Union[str, Any]					,   lowercase_:				Optional[int]					,   lowercase_:				Any      )  ->   Dict:
	A__							:					Tuple       =	XGBRegressor(verbosity=0					,   random_state=42      )
	xgb.fit(lowercase_					,   lowercase_      )
	# Predict target for test data
	A__							:					Optional[Any]       =	xgb.predict(lowercase_      )
	A__							:					Optional[Any]       =	predictions.reshape(len(lowercase_      )					,   1      )
	return predictions

def 		UpperCamelCase      ()  ->   Dict:
	A__							:					str       =	fetch_california_housing()
	A__     ,     A__							:					Union[str, Any]       =	data_handling(lowercase_      )
	A__     ,     A__     ,     A__     ,     A__							:					Tuple       =	train_test_split(
	    lowercase_					,   lowercase_					,   test_size=0.25					,   random_state=1      )
	A__							:					Union[str, 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 warnings

from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor


A_ :				Union[str, Any]						 =    logging.get_logger(__name__)



class 					_a		(__magic_name__       ):


					'''simple docstring'''






					def __init__(				self					, *A__					, **A__    ):
						warnings.warn(
						    """The class PoolFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
						    """ Please use PoolFormerImageProcessor instead."""					, A__					, )
						super().__init__(*A__					, **A__    )



