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.

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

Train on 25% and 50% #224

Open
chengsoonong opened this issue Mar 17, 2017 · 2 comments
Open

Train on 25% and 50% #224

chengsoonong opened this issue Mar 17, 2017 · 2 comments
Milestone

Comments

@chengsoonong
Copy link
Owner

No description provided.

@MatthewJA MatthewJA modified the milestone: MNRAS Mar 26, 2017
@MatthewJA
Copy link
Collaborator

Train a CNN on 25% and 50% of the full RGZ set. Test on RGZ & Norris with Norris labels. See if there's a difference.

@MatthewJA
Copy link
Collaborator

For LR, not for a CNN, but here's a plot of accuracy against the training set size (in radio objects). Looks like we need at least 100 radio objects to peak for LR — that's on the same order as the number of objects cross-identified by Norris et al. I suspect the CNN will converge slower.

image

MatthewJA added a commit that referenced this issue Apr 26, 2017
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants