





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


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase    ,       lowerCAmelCase    ,       lowerCAmelCase					):
							_UpperCamelCase              =						XGBRegressor(verbosity=0    ,       random_state=42					)
							xgb.fit(lowerCAmelCase    ,       lowerCAmelCase					)
							# Predict target for test data
							_UpperCamelCase              =						xgb.predict(lowerCAmelCase					)
							_UpperCamelCase              =						predictions.reshape(len(lowerCAmelCase					)    ,       1					)
							return predictions


def     SCREAMING_SNAKE_CASE			(      ):
							_UpperCamelCase              =						fetch_california_housing()
							_UpperCamelCase              =						data_handling(lowerCAmelCase					)
							_UpperCamelCase              =						train_test_split(
							    lowerCAmelCase    ,       lowerCAmelCase    ,       test_size=0.2_5    ,       random_state=1					)
							_UpperCamelCase              =						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()













def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						[]
       if len(lowerCAmelCase					) == 1:
              return [nums.copy()]
       for _ in range(len(lowerCAmelCase					)					):
              _UpperCamelCase              =						nums.pop(0					)
              _UpperCamelCase              =						permute(lowerCAmelCase					)
              for perm in permutations:
                     perm.append(lowerCAmelCase					)
              result.extend(lowerCAmelCase					)
              nums.append(lowerCAmelCase					)
       return result


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):

       def backtrack(lowerCAmelCase					):
              if start == len(lowerCAmelCase					) - 1:
                     output.append(nums[:]					)
              else:
                     for i in range(lowerCAmelCase    ,       len(lowerCAmelCase					)					):
                            _UpperCamelCase       ,		_UpperCamelCase              =						nums[i], nums[start]
                            backtrack(start + 1					)
                            _UpperCamelCase       ,		_UpperCamelCase              =						nums[i], nums[start]  # backtrack

       _UpperCamelCase              =						[]
       backtrack(0					)
       return output


if __name__ == "__main__":
       import doctest

       # use res to print the data in permute2 function
       lowercase    : Optional[Any]    	=  permutea([1, 2, 3])
       print(res)
       doctest.testmod()






