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Statistical Machine Learning Project

Label Propagation Methods

Team Members


Description


The goal of this project is to implement a graph label propagation method to study and classify image data.

figure


Virtual environment


Use the following command lines to create and use venv python package:

python3.10 -m venv venv

Then use the following to activate the environment:

source venv/bin/activate

You can now use pip to install any packages you need for the project and run python scripts, usually through a requirements.txt:

python -m pip install -r requirements.txt

When you are finished, you can stop the environment by running:

deactivate

Project Organization


├── README.md          -- Top-level README.
│
├── notebooks          -- Jupyter notebooks.
│
├── articles           -- Related articles and useful references.
│
├── reports            -- Notes and report (Latex, pdf).
│ 
├── figures            -- Optional graphics and figures to be included in the report.
│
├── data               -- data sets.
│
├── model_saves        -- stored trained models.
│
├── requirements.txt   -- Requirements file for reproducibility.
│
└── src                -- Source code for use in this project.
    │
    ├── __init__.py    -- Makes src a Python package (and not just a module)
    │
    ├── random_forest  -- script for the random forest regressor
    │
    ├── st_app         -- structure for streamlit application
    │
    ├── st_utils       -- helper functions called in st_app.py
    │
    ├── helpers        -- various small helper functions
    │
    └── visualization  -- visual features for exploratory data analysis