


import numpy

# List of input, output pairs
lowerCAmelCase__    :Optional[Any]       =				(
    ((5, 2, 3), 1_5),
    ((6, 5, 9), 2_5),
    ((1_1, 1_2, 1_3), 4_1),
    ((1, 1, 1), 8),
    ((1_1, 1_2, 1_3), 4_1),
)
lowerCAmelCase__    :List[str]       =				(((5_1_5, 2_2, 1_3), 5_5_5), ((6_1, 3_5, 4_9), 1_5_0))
lowerCAmelCase__    :Any       =				[2, 4, 1, 5]
lowerCAmelCase__    :Tuple       =				len(train_data)
lowerCAmelCase__    :Tuple       =				0.009

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						str="train"			)    ->						Optional[int]:


							'''simple docstring'''





							return calculate_hypothesis_value(a__     ,    a__			) - output(
							    a__     ,    a__			)

def 			lowerCAmelCase__					(     a__:						Optional[Any]			)    ->						Tuple:


							'''simple docstring'''





							_UpperCAmelCase											=     0
							for i in range(len(a__			) - 1			):
														hyp_val += data_input_tuple[i] * parameter_vector[i + 1]
							hyp_val += parameter_vector[0]
							return hyp_val

def 			lowerCAmelCase__					(     a__:						List[Any]     ,    a__:						List[str]			)    ->						Tuple:


							'''simple docstring'''





							if data_set == "train":
														return train_data[example_no][1]
							elif data_set == "test":
														return test_data[example_no][1]
							return None

def 			lowerCAmelCase__					(     a__:						Tuple     ,    a__:						int			)    ->						Tuple:


							'''simple docstring'''





							if data_set == "train":
														return _hypothesis_value(train_data[example_no][0]			)
							elif data_set == "test":
														return _hypothesis_value(test_data[example_no][0]			)
							return None

def 			lowerCAmelCase__					(     a__:						Optional[int]     ,    a__:						Tuple=m			)    ->						str:


							'''simple docstring'''





							_UpperCAmelCase											=     0
							for i in range(a__			):
														if index == -1:
																					summation_value += _error(a__			)
														else:
																					summation_value += _error(a__			) * train_data[i][0][index]
							return summation_value

def 			lowerCAmelCase__					(     a__:						Optional[int]			)    ->						Any:


							'''simple docstring'''





							_UpperCAmelCase											=     summation_of_cost_derivative(a__     ,    a__			) / m
							return cost_derivative_value

def 			lowerCAmelCase__					(     )    ->						List[Any]:


							'''simple docstring'''





							global parameter_vector
							# Tune these values to set a tolerance value for predicted output
							_UpperCAmelCase											=     0.000_002
							_UpperCAmelCase											=     0
							_UpperCAmelCase											=     0
							while True:
														j += 1
														_UpperCAmelCase											=     [0, 0, 0, 0]
														for i in range(0     ,    len(a__			)			):
																					_UpperCAmelCase											=     get_cost_derivative(i - 1			)
																					_UpperCAmelCase											=     (
																					    parameter_vector[i] - LEARNING_RATE * cost_derivative
																					)
														if numpy.allclose(
														    a__     ,    a__     ,    atol=a__     ,    rtol=a__     ,    ):
																					break
														_UpperCAmelCase											=     temp_parameter_vector
							print(('Number of iterations:', j)			)

def 			lowerCAmelCase__					(     )    ->						List[Any]:


							'''simple docstring'''





							for i in range(len(a__			)			):
														print(('Actual output value:', output(a__     ,    'test'			))			)
														print(('Hypothesis output:', calculate_hypothesis_value(a__     ,    'test'			))			)


if __name__ == "__main__":
		run_gradient_descent()
		print('''\nTesting gradient descent for a linear hypothesis function.\n''')
		test_gradient_descent()




def 			lowerCAmelCase__					(     a__:						Optional[int]			)    ->						Optional[int]:


							'''simple docstring'''





							_UpperCAmelCase											=     len(a__			)
							for i in range(length - 1			):
														_UpperCAmelCase											=     i
														for k in range(i + 1     ,    a__			):
																					if collection[k] < collection[least]:
																												_UpperCAmelCase											=     k
														if least != i:
																					_UpperCAmelCase						,			_UpperCAmelCase											=     (collection[i], collection[least])
							return collection


if __name__ == "__main__":
		lowerCAmelCase__    :List[str]       =				input('''Enter numbers separated by a comma:\n''').strip()
		lowerCAmelCase__    :Any       =				[int(item) for item in user_input.split(''',''')]
		print(selection_sort(unsorted))
