


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 		__lowerCAmelCase   (							_UpperCamelCase		)    ->				tuple:






      '''simple docstring'''

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

def 		__lowerCAmelCase   (							_UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase		)    ->				np.ndarray:






      '''simple docstring'''

      lowerCamelCase__:						int							   = XGBRegressor(verbosity=0       ,			random_state=42		)
      xgb.fit(lowerCamelCase_       ,			lowerCamelCase_		)
      # Predict target for test data
      lowerCamelCase__:						int							   = xgb.predict(lowerCamelCase_		)
      lowerCamelCase__:						Optional[Any]							   = predictions.reshape(len(lowerCamelCase_		)       ,			1		)
      return predictions

def 		__lowerCAmelCase   (							)    ->				None:






      '''simple docstring'''

      lowerCamelCase__:						Tuple							   = fetch_california_housing()
      lowerCamelCase__:						Any							   = data_handling(lowerCamelCase_		)
      lowerCamelCase__:						Optional[Any]							   = train_test_split(
          lowerCamelCase_       ,			lowerCamelCase_       ,			test_size=0.25       ,			random_state=1		)
      lowerCamelCase__:						Optional[int]							   = xgboost(lowerCamelCase_       ,			lowerCamelCase_       ,			lowerCamelCase_		)
      # Error printing
      print(f"""Mean Absolute Error : {mean_absolute_error(lowerCamelCase_       ,			lowerCamelCase_		)}"""		)
      print(f"""Mean Square Error  : {mean_squared_error(lowerCamelCase_       ,			lowerCamelCase_		)}"""		)


if __name__ == "__main__":
      import doctest

      doctest.testmod(verbose=True)
      main()










import os

try:
 from .build_directory_md import good_file_paths
except ImportError:
 from build_directory_md import good_file_paths  # type: ignore

SCREAMING_SNAKE_CASE			: int				   =					list(good_file_paths())
assert filepaths, "good_file_paths() failed!"

SCREAMING_SNAKE_CASE			: Dict				   =					[file for file in filepaths if file != file.lower()]
if upper_files:
 print(F"{len(upper_files)} files contain uppercase characters:")
 print("\n".join(upper_files) + "\n")

SCREAMING_SNAKE_CASE			: List[Any]				   =					[file for file in filepaths if " " in file]
if space_files:
 print(F"{len(space_files)} files contain space characters:")
 print("\n".join(space_files) + "\n")

SCREAMING_SNAKE_CASE			: Any				   =					[file for file in filepaths if "-" in file]
if hyphen_files:
 print(F"{len(hyphen_files)} files contain hyphen characters:")
 print("\n".join(hyphen_files) + "\n")

SCREAMING_SNAKE_CASE			: str				   =					[file for file in filepaths if os.sep not in file]
if nodir_files:
 print(F"{len(nodir_files)} files are not in a directory:")
 print("\n".join(nodir_files) + "\n")

SCREAMING_SNAKE_CASE			: Tuple				   =					len(upper_files + space_files + hyphen_files + nodir_files)
if bad_files:
 import sys

 sys.exit(bad_files)


