





import numpy

# List of input, output pairs
_a						=   (
    ((5, 2, 3), 15),
    ((6, 5, 9), 25),
    ((11, 12, 13), 41),
    ((1, 1, 1), 8),
    ((11, 12, 13), 41),
)
_a						=   (((515, 22, 13), 555), ((61, 35, 49), 150))
_a						=   [2, 4, 1, 5]
_a						=   len(train_data)
_a						=   0.009





def lowerCAmelCase__(__snake_case ,__snake_case="train"							)       ->   Optional[int]:







	'''simple docstring'''







	return calculate_hypothesis_value(__snake_case ,__snake_case							) - output(
	    __snake_case ,__snake_case							)





def lowerCAmelCase__(__snake_case							)       ->   List[Any]:







	'''simple docstring'''







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





def lowerCAmelCase__(__snake_case ,__snake_case							)       ->   List[Any]:







	'''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__(__snake_case ,__snake_case							)       ->   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__(__snake_case ,__snake_case=m							)       ->   List[str]:







	'''simple docstring'''







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





def lowerCAmelCase__(__snake_case							)       ->   List[Any]:







	'''simple docstring'''







	lowerCamelCase__              =	summation_of_cost_derivative(__snake_case ,__snake_case							) / m
	return cost_derivative_value





def lowerCAmelCase__()       ->   List[str]:







	'''simple docstring'''







	global parameter_vector
	# Tune these values to set a tolerance value for predicted output
	lowerCamelCase__              =	0.0_0_0_0_0_2
	lowerCamelCase__              =	0
	lowerCamelCase__              =	0
	while True:
		j += 1
		lowerCamelCase__              =	[0, 0, 0, 0]
		for i in range(0 ,len(__snake_case							)							):
			lowerCamelCase__              =	get_cost_derivative(i - 1							)
			lowerCamelCase__              =	(
			    parameter_vector[i] - LEARNING_RATE * cost_derivative
			)
		if numpy.allclose(
		    __snake_case ,__snake_case ,atol=__snake_case ,rtol=__snake_case ,):
			break
		lowerCamelCase__              =	temp_parameter_vector
	print(('''Number of iterations:''', j)							)





def lowerCAmelCase__()       ->   Tuple:







	'''simple docstring'''







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


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










import string
from math import logaa





def lowerCAmelCase__(__snake_case ,__snake_case							)       ->   int:







	'''simple docstring'''







	lowerCamelCase__              =	document.translate(
	    str.maketrans('''''' ,'''''' ,string.punctuation							)							).replace('''\n''' ,''''''							)
	lowerCamelCase__              =	document_without_punctuation.split(''' '''							)  # word tokenization
	return len([word for word in tokenize_document if word.lower() == term.lower()]							)





def lowerCAmelCase__(__snake_case ,__snake_case							)       ->   tuple[int, int]:







	'''simple docstring'''







	lowerCamelCase__              =	corpus.lower().translate(
	    str.maketrans('''''' ,'''''' ,string.punctuation							)							)  # strip all punctuation and replace it with ''
	lowerCamelCase__              =	corpus_without_punctuation.split('''\n'''							)
	lowerCamelCase__              =	term.lower()
	return (len([doc for doc in docs if term in doc]							), len(__snake_case							))





def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case=False							)       ->   float:







	'''simple docstring'''







	if smoothing:
		if n == 0:
			raise ValueError('''log10(0) is undefined.'''							)
		return round(1 + logaa(n / (1 + df)							) ,3							)

	if df == 0:
		raise ZeroDivisionError('''df must be > 0'''							)
	elif n == 0:
		raise ValueError('''log10(0) is undefined.'''							)
	return round(logaa(n / df							) ,3							)





def lowerCAmelCase__(__snake_case ,__snake_case							)       ->   float:







	'''simple docstring'''







	return round(tf * idf ,3							)



