Created
June 24, 2020 06:19
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def run_lr(res,data): | |
# Note: data should be given in pandas format, as shwon below: | |
''' | |
Brain_weight Body_weight | |
62.00 1320.0 | |
55.50 175.0 | |
35.00 56.0 | |
52.16 440.0 | |
0.28 1.9 | |
''' | |
points=data | |
learning_rate = 0.000001 | |
initial_b = 0 # initial y-intercept guess | |
initial_m = 0 # initial slope guess | |
num_iterations = 1000 | |
print ("Starting gradient descent at b = {0}, m = {1}, error = {2}".format(initial_b, initial_m, compute_error_for_line_given_points(initial_b, initial_m, array(points)))) | |
print ("Running...") | |
[b, m] = gradient_descent_runner(points, initial_b, initial_m, learning_rate, num_iterations) | |
print ("After {0} iterations b = {1}, m = {2}, error = {3}".format(num_iterations, b, m, compute_error_for_line_given_points(b, m, array(points)))) | |
print(b) | |
print(m) | |
res.append(b) | |
res.append(m) |
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