Statistical Machine Learning Project

Label Propagation Methods

Team Members

• Julia Bierent
• Luca Nyckees
• Blerton Rashiti

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Description

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

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Virtual environment

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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

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Project Organization

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