Assigned pulearning doesn't change the results much

[sharifza]

From what I understand if I assign pulearning = 1 (in a binary classification problem), it should imply that the class of ones has no noise. Still after training, i get the following output from the confident_joint, est_py, est_nm and est_inv respectively as:

[[ 3216. 1179.]
[16989. 14594.]]

[0.79313136 0.20686864]

[[0.15916852 0.07474799]
[0.84083148 0.92525201]]

[[0.73174061 0.53791597]
[0.26825939 0.46208403]]

Is there any other way to make sure no data points from class 1 are considered as noisy?

Thanks.

[mmdknr]

Bump!

[mmdknr]

Same issue :(

[cgnorthcutt]

Hi, thanks for the suggestion. Would either of you like to submit a pull request? It should look something of the form,

if K == 2 and pulearning:
  # Do stuff

[cgnorthcutt]

@mmdknr @sharifza -- fixed! See: cgnorthcutt@12dd1ac#diff-1cfd7e0a508d041378eb0e2de1f5ab3a

Closing.