



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     a(      A       :    dict       )		->       tuple:
					"""simple docstring"""





					return (data["data"], data["target"])






def     a(      A       :    np.ndarray ,     A       :    np.ndarray ,     A       :    np.ndarray       )		->       np.ndarray:
					"""simple docstring"""





					a					     =   XGBRegressor(verbosity=0 ,     random_state=42       )
					xgb.fit(A ,     A       )
					# Predict target for test data
					a					     =   xgb.predict(A       )
					a					     =   predictions.reshape(len(A       ) ,     1       )
					return predictions






def     a(      )		->       None:
					"""simple docstring"""





					a					     =   fetch_california_housing()
					a     ,				a					     =   data_handling(A       )
					a     ,				a     ,				a     ,				a					     =   train_test_split(
					    A ,     A ,     test_size=0.25 ,     random_state=1       )
					a					     =   xgboost(A ,     A ,     A       )
					# Error printing
					print(f'''Mean Absolute Error : {mean_absolute_error(A ,     A       )}'''       )
					print(f'''Mean Square Error  : {mean_squared_error(A ,     A       )}'''       )


if __name__ == "__main__":
				import doctest

				doctest.testmod(verbose=True)
				main()





def     a(      A       :    int       )		->       str:
					"""simple docstring"""





					if number > 0:
										raise ValueError("input must be a negative integer"       )
					a					     =   len(bin(A       )[3:]       )
					a					     =   bin(abs(A       ) - (1 << binary_number_length)       )[3:]
					a					     =   (
					    (
					        "1"
					        + "0" * (binary_number_length - len(A       ))
					        + twos_complement_number
					    )
					    if number < 0
					    else "0"
					)
					return "0b" + twos_complement_number


if __name__ == "__main__":
				import doctest

				doctest.testmod()
