Comments (2)
I do not see how I can define a pruner for something like logistic regression. I do not see what the step value would be. I currently set it to 1 which in essence does no pruning I believe.
In an iterative algorithm like gradient descent, step
would be iteration or step and value
would be validation loss or some metric which should have consistent direction with the objective value.
Also, am I correct that I can tune KNN by using n_neighbors as the step?
It sounds wrong.
from optuna-examples.
Anyway, this question is not related to this repo. Please use https://github.com/optuna/optuna/discussions to ask questions about optuna.
from optuna-examples.
Related Issues (20)
- AttributeError: 'Trainer' object has no attribute 'training_type_plugin' HOT 5
- Implement cross-validation examples for Optuna Terminator 🤖 HOT 3
- Add `plot_rank` and `plot_timeline` to visualisation examples HOT 2
- Trial Fail HOT 1
- Optuna DDP with Slurm Cluster HOT 1
- License of the optuna-examples repo? HOT 2
- optuna.integration.XGBoostPruningCallback is not xgboost TrainingCallback HOT 2
- Updating the PyTorch Lightning example to >= 2.0 HOT 5
- Pruning Not Working in Pytorch HOT 1
- Support Lighting instead/besides Pytorch Lighting HOT 1
- Flax example HOT 2
- optuna-examples/xgboost /xgboost_integration.py error HOT 1
- Add `README.md` to `./dashboard` HOT 3
- Add Python 3.12 to the CI HOT 8
- Add README to each directory if it contains multiple examples HOT 2
- XGBoost callback problem HOT 2
- The problem of DDP training with pytorch lightning HOT 1
- NSGAIISampler number trials per generation HOT 1
- intermediate values and objective value use different metrics in `LightGBMPruningCallback` HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from optuna-examples.