



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_(lowerCamelCase_    ) ->       tuple:
						return (data["data"], data["target"])

def    lowerCamelCase_(lowerCamelCase_    ,   lowerCamelCase_    ,   lowerCamelCase_    ) ->       np.ndarray:
						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    lowerCamelCase_() ->       None:
						UpperCAmelCase         =     fetch_california_housing()
						UpperCAmelCase       ,		UpperCAmelCase         =     data_handling(lowerCamelCase_    )
						UpperCAmelCase       ,		UpperCAmelCase       ,		UpperCAmelCase       ,		UpperCAmelCase         =     train_test_split(
						    lowerCamelCase_    ,   lowerCamelCase_    ,   test_size=0.25    ,   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    lowerCamelCase_(lowerCamelCase_    ,   lowerCamelCase_    ) ->       list[int]:
						UpperCAmelCase         =     int(lowerCamelCase_    )

						# Initialize Result
						UpperCAmelCase         =     []

						# Traverse through all denomination
						for denomination in reversed(lowerCamelCase_    ):
												# Find denominations
												while int(lowerCamelCase_    ) >= int(lowerCamelCase_    ):
																		total_value -= int(lowerCamelCase_    )
																		answer.append(lowerCamelCase_    )  # Append the "answers" array

						return answer


# Driver Code
if __name__ == "__main__":
		__lowerCamelCase     :							Optional[int]  							=				[]
		__lowerCamelCase     :							Dict  							=				"0"

		if (
		    input("Do you want to enter your denominations ? (yY/n): ").strip().lower()
		    == "y"
		):
				__lowerCamelCase     :							List[Any]  							=				int(input("Enter the number of denominations you want to add: ").strip())

				for i in range(0, n):
						denominations.append(int(input(F'''Denomination {i}: ''').strip()))
				__lowerCamelCase     :							str  							=				input("Enter the change you want to make in Indian Currency: ").strip()
		else:
				# All denominations of Indian Currency if user does not enter
				__lowerCamelCase     :							Optional[int]  							=				[1, 2, 5, 10, 20, 50, 100, 500, 2_000]
				__lowerCamelCase     :							Optional[int]  							=				input("Enter the change you want to make: ").strip()

		if int(value) == 0 or int(value) < 0:
				print("The total value cannot be zero or negative.")

		else:
				print(F'''Following is minimal change for {value}: ''')
				__lowerCamelCase     :							Union[str, Any]  							=				find_minimum_change(denominations, value)
				# Print result
				for i in range(len(answer)):
						print(answer[i], end=" ")



