Sample selection
- Langage dominant
- Jupyter Notebook
- Étoiles
- 551
- Forks
- 143
- Métriques de merge des PR
- Aucune PR mergée en 30 j
Description
I would like to ask if AutoX has any plans for sample selection?
Now many data sets are so large that the computing power of individuals and small companies cannot afford.
Can a part of the data be selected for training to approximate the effect of full data training?
Guide de contribution
Aucun guide de contribution indexé pour ce dépôt
Piste de recherche
Look at the AutoX codebase for data loading and preprocessing modules to understand the current pipeline. Investigate existing sampling techniques or if any are implemented. Determine how to integrate a sample selection feature that works with large datasets and evaluate its impact on training performance.
Rédigé par le modèle d'indexation à partir du texte de l'issue.
Évaluation
- Stack technique
- jupyter-notebook, machine-learning, python
- Domaine
- data-engineering, machine-learning
- Type d'issue
- Fonctionnalité
- Difficulté
- 4/5
- Temps estimé
- 3-5 jours
- Activité
- À l'abandon
- Clarté
- Plutôt claire
- Accessibilité débutants
- 35/100