https://github.com/allencellmodeling/lightgbm_mito
mitotic classification using features data and gradient boosted decision trees
https://github.com/allencellmodeling/lightgbm_mito
Last synced: 12 months ago
JSON representation
mitotic classification using features data and gradient boosted decision trees
- Host: GitHub
- URL: https://github.com/allencellmodeling/lightgbm_mito
- Owner: AllenCellModeling
- Created: 2017-11-09T19:54:11.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2017-11-14T23:57:06.000Z (over 8 years ago)
- Last Synced: 2025-01-02T23:14:20.129Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 2.75 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Mitotic classification using gradient boosted decision trees
This repository contains a notebook `lightgbm_mito.ipynb` and some scaffolding to facilitate reproducibility.
Most importantly, the `Dockerfile` creates an environment in which the notebook can be run.
You can either build the docker image yourself with
```bash build.sh```
or pull it from docker hub with
```docker pull rorydm/mito_gbdts```
To run the notebook (you might want to do this in a screen session):
```bash run.sh ```
then copy the link jupyter gives you to your browser, replacing the default port `8888` with ``.
If you're working remotely, you''l have to forward the remote `` to your local machine.
Once the docker process is running, open the notebook, and `Kernel > Restart & Run All` should work.