https://github.com/jdhao/logistic-regression
logistic regression from scratch
https://github.com/jdhao/logistic-regression
logistic-regression machine-learning
Last synced: 6 months ago
JSON representation
logistic regression from scratch
- Host: GitHub
- URL: https://github.com/jdhao/logistic-regression
- Owner: jdhao
- Created: 2022-04-04T06:37:25.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-10-17T20:43:19.000Z (almost 4 years ago)
- Last Synced: 2025-12-02T02:13:58.055Z (8 months ago)
- Topics: logistic-regression, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 279 KB
- Stars: 2
- Watchers: 1
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Description
This is my implementation for Logistic regression for a classification task,
dropout during training is also included.
Dataset used in training and evaluation is [breast cancer dataset](https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html).
The model training is done using SGD (stochastic gradient descent).
You can check the derivation of derivative for weight in `doc.pdf`.
# Dependency
Run the following command to install dependencies:
```
pip install -r requirements.txt
```
# How to run
The complete code is in `run_sgd.py`:
```
python run_sgd.py
```