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)

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SaniyaAbushakimova%2FA-Study-of-Sigmoid-based-Multi-class-Logistic-Regression

Stars: 2
Forks: 0
Open issues: 0

License: None
Language: Jupyter Notebook
Size: 835 KB
Dependencies parsed at: Pending

Created at: over 3 years ago
Updated at: 11 months ago
Pushed at: 11 months ago
Last synced at: 3 months ago

Topics: aaai, multiclass-logistic-regression, python, research, statistical-learning

ecosyste.ms

Data

Tools

Indexes

Applications

Experiments

Repos

GitHub / SaniyaAbushakimova / A-Study-of-Sigmoid-based-Multi-class-Logistic-Regression