iamarchisha / iamarchisha/RDScML
Dealing with overfitting using regularization techniques
- Dominant language
- Jupyter Notebook
- Stars
- 2
- Forks
- 12
- PR merge metrics
- No merged PRs in 30d
Description
Explore different regularization techniques to prevent the model used from overfitting. Use any technique and perform a complete POC on the same.
- How did you analyse that the model was overfitting?
- What was the need to use this particular approach?
- Explain how the approach used was suitable for the dataset.
- Compare the model performance before and after performing regularization.
Clearly explain what function is being performed in each cell. Give enough explanation where necessary.
Contributor guide
No contributing guide indexed for this repository
Research direction
No specific notebook, model, or dataset is named. Start by locating the existing model notebook and dataset in the repository, then establish how overfitting is measured before selecting and documenting one regularization approach. Done means the notebook explains each cell and compares model performance before and after regularization.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100