Can we use online learning in Qlib?
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 48.7k
- Forks
- 7.7k
- PR merge metrics
- No merged PRs in 30d
Description
❓ Questions and Help
Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms. It is also used in situations where it is necessary for the algorithm to dynamically adapt to new patterns in the data, or when the data itself is generated as a function of time, e.g., stock price prediction.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points; begin by clarifying the desired online-learning workflow and reviewing Qlib's existing machine-learning modeling paradigms. Done would require an agreed scope and a defined way to verify support for out-of-core or time-adaptive training.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100