Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Handling non-convergence in AffinityPropagation #9

Open
zdk123 opened this issue Apr 26, 2022 · 0 comments
Open

Handling non-convergence in AffinityPropagation #9

zdk123 opened this issue Apr 26, 2022 · 0 comments
Assignees
@jorgecnavarrom
Labels
BiG-SCAPE 1 Relates to BiG-SCAPE version 1.0 no-stale Prevent this issue from going stale

Comments

@zdk123
Copy link

zdk123 commented Apr 26, 2022

Related to #2. In the latest version of scikit-learn:

When fit does not converge, cluster_centers_ becomes an empty array and all training samples will be labelled as -1. In addition, predict will then label every sample as -1.

Previously, the cluster_centers_ output was None. Therefore, bigscape is no longer handling convergence failures correctly.
@jorgecnavarrom jorgecnavarrom self-assigned this May 2, 2022
@jorgecnavarrom jorgecnavarrom mentioned this issue May 25, 2022
Closed
@zdk123 zdk123 closed this as completed Nov 15, 2022
@zdk123 zdk123 reopened this Nov 15, 2022
@jorgecnavarrom jorgecnavarrom added the BiG-SCAPE 1 Relates to BiG-SCAPE version 1.0 label Mar 16, 2023
@adraismawur adraismawur added the no-stale Prevent this issue from going stale label Sep 13, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees

@jorgecnavarrom jorgecnavarrom

Labels
BiG-SCAPE 1 Relates to BiG-SCAPE version 1.0 no-stale Prevent this issue from going stale
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
3 participants
@zdk123 @jorgecnavarrom @adraismawur