🚀 Running the Experiment

This project uses a Conda-based reproducible environment
(Python 3.12, PyTorch 2.7.0, scikit-learn 1.7.2).

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1️⃣ Environment Setup (Required)

Create the Conda Environment

From the project root directory, run:

conda env create -f environment.yml

This will create a Conda environment named:masterthesis Step 2: Activate the Environment

conda activate masterthesis

Step 3: Verify Installation (Optional but Recommended)

python --version
python -c "import torch; print(torch.__version__)"
python -c "import sklearn; print(sklearn.__version__)"

Expected versions:

Python 3.12

PyTorch 2.7.0

scikit-learn 1.7.2

📊 2. Download the Dataset

Download public log datasets from:

https://github.com/logpai/loghub

Place the downloaded datasets inside the project's:

data/

directory.

⚙️ 3. Configure the Experiment

Edit the configuration file:

config.py

This file stores the experimental settings, including:

-Dataset paths

--Model paths

Training schemes

-Hyperparameters

-Grouping strategies

-Adjust these settings according to your experimental setup.

🧠 4. Run Training

To start training the model:

python main.py