https://github.com/saniyaabushakimova/a-study-of-sigmoid-based-multi-class-logistic-regression
Investigated how multi-class logistic regression would perform if the activation function was changed from softmax to sigmoid. It included mathematical analysis and empirical evaluation, such as rewriting the model from scratch. Tech: Python (scikit-learn, pandas)
https://github.com/saniyaabushakimova/a-study-of-sigmoid-based-multi-class-logistic-regression
aaai multiclass-logistic-regression python research statistical-learning
Last synced: 7 months ago
JSON representation
Investigated how multi-class logistic regression would perform if the activation function was changed from softmax to sigmoid. It included mathematical analysis and empirical evaluation, such as rewriting the model from scratch. Tech: Python (scikit-learn, pandas)
- Host: GitHub
- URL: https://github.com/saniyaabushakimova/a-study-of-sigmoid-based-multi-class-logistic-regression
- Owner: SaniyaAbushakimova
- Created: 2021-12-08T09:20:40.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2024-07-13T22:13:28.000Z (about 1 year ago)
- Last Synced: 2024-07-13T23:25:23.347Z (about 1 year ago)
- Topics: aaai, multiclass-logistic-regression, python, research, statistical-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 835 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
Project completed on Dec 9, 2021.
### Purpose
- Investigate how sigmoid-based multi-class logistic regression would perform compared to softmax_based one.
### Content
- `Final Project/Final_project_report.pdf` - Report (AAAI format) that contains description and results of the work done.
- `Final Project/Final_project_solution.ipynb` - Jupyther Notebook with Data exploration, training procedures and experiments.
- `Final Project/Preprocessing.ipynb` - Jupyter Notebook with data preprocessing.