Thanks for the repo.
I believe that there is a bug in the current implementation of EM, this line in particular.
It calculates the relative difference between the previous and current predictions. However, it should calculate the absolute difference, ie
delta = np.abs(col[x_i]-previous)/previous
The current implementation will just break if the current is less than the previous value, as this will result in a negative value which is clearly less than 10%.
For example, if:
col[x_i] = 1
previous = 1000
delta = -0.999 # delta < 0.1 will return True hence it will assume convergence despite the huge difference
Hello,
Thanks for the repo. I believe that there is a bug in the current implementation of EM, this line in particular.
It calculates the relative difference between the previous and current predictions. However, it should calculate the absolute difference, ie
delta = np.abs(col[x_i]-previous)/previousThe current implementation will just break if the current is less than the previous value, as this will result in a negative value which is clearly less than 10%.
For example, if: col[x_i] = 1 previous = 1000 delta = -0.999 # delta < 0.1 will return True hence it will assume convergence despite the huge difference
Best regards