weight = np.array([car[4] for car in data], dtype=np.float64)
acceleration = np.array([car[5] for car in data], dtype=np.float64)
model_year = np.array([car[6] for car in data], dtype=np.float64)
origin = np.array([car[7] for car in data], dtype=np.float64)
corr_vector_to_mpg = [
correlation(mpg, cylinders),
correlation(mpg, displacement),
correlation(mpg, horsepower),
correlation(mpg, weight),
correlation(mpg, acceleration),
correlation(mpg, model_year)
]
abs_corr_vector = [abs(x) for x in corr_vector_to_mpg]
weight_to_mpg_m, weight_to_mpg_b = best_fit_line(weight, mpg)
cylinder_to_mpg_m, cylinder_to_mpg_b = best_fit_line(cylinders, mpg)
displacement_to_mpg_m, displacement_to_mpg_b = best_fit_line(displacement, mpg)
horsepower_to_mpg_m, horsepower_to_mpg_b = best_fit_line(horsepower, mpg)
acceleration_to_mpg_m, acceleration_to_mpg_b = best_fit_line(acceleration, mpg)
model_year_to_mpg_m, model_year_to_mpg_b = best_fit_line(model_year, mpg)
mpg_equations = [(cylinder_to_mpg_m, cylinder_to_mpg_b),
(displacement_to_mpg_m, displacement_to_mpg_b),
(horsepower_to_mpg_m, horsepower_to_mpg_b),
(weight_to_mpg_m, weight_to_mpg_b),
(acceleration_to_mpg_m, acceleration_to_mpg_b),
(model_year_to_mpg_m, model_year_to_mpg_b)]
possibilities = find_range_adjustment_results(data, mpg_equations,
abs_corr_vector)
mpgData = 'data/auto-mpg.data.txt'
dataKey = ['MPG', 'Cylinders', 'Displacement', 'Horsepower', 'Weight', 'Acceleration', 'Model Year']
with open(mpgData) as f:
content = f.readlines()
data = [[float(x) for x in line.split()[0:7]] for line in content]
mpg = np.array([car[0] for car in data], dtype=np.float64)
cylinders = np.array([car[1] for car in data], dtype=np.float64)
displacement = np.array([car[2] for car in data], dtype=np.float64)
horsepower = np.array([car[3] for car in data], dtype=np.float64)
weight = np.array([car[4] for car in data], dtype=np.float64)
acceleration = np.array([car[5] for car in data], dtype=np.float64)
model_year = np.array([car[6] for car in data], dtype=np.float64)
weight_to_mpg_m, weight_to_mpg_b = best_fit_line(weight, mpg)
cylinder_to_mpg_m, cylinder_to_mpg_b = best_fit_line(cylinders, mpg)
displacement_to_mpg_m, displacement_to_mpg_b = best_fit_line(displacement, mpg)
horsepower_to_mpg_m, horsepower_to_mpg_b = best_fit_line(horsepower, mpg)
acceleration_to_mpg_m, acceleration_to_mpg_b = best_fit_line(acceleration, mpg)
model_year_to_mpg_m, model_year_to_mpg_b = best_fit_line(model_year, mpg)
mpg_equations = [(cylinder_to_mpg_m, cylinder_to_mpg_b), (displacement_to_mpg_m, displacement_to_mpg_b), (horsepower_to_mpg_m, horsepower_to_mpg_b), (weight_to_mpg_m, weight_to_mpg_b), (acceleration_to_mpg_m, acceleration_to_mpg_b), (model_year_to_mpg_m, model_year_to_mpg_b)]
correlation_to_mpg_vector = [correlation(mpg, cylinders), correlation(mpg, displacement), correlation(mpg, horsepower), correlation(mpg, weight), correlation(mpg, acceleration), correlation(mpg, model_year)]
abs_correlation_vector = [abs(x) for x in correlation_to_mpg_vector]
test_value_vector = [num*(softmax_weight) for num in abs_correlation_vector]
weighting_values = softmax(test_value_vector)
predicted_mpgs_list = []