MORGAN-MER is a Python-based project designed for recommending modeling operations from XES models. The system provides functionalities for training, recommendation, and cross-validation of models using various configurations.
- Training Data Preparation: Process and encode XES models for system training.
- Recommendation Engine: Generate recommendations based on the trained knowledge base or session data.
- Cross-Validation: Perform cross-validation to evaluate model performance.
- Hepsycode Dataset Processing: Parse and process the hepsycode dataset.
To install the project dependencies, run:
pip install -r requirements.txt
The main script main.py supports different modes of operation:
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Training Mode: Prepare data for training
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Recommendation Mode: Run the recommender on the knowledge base
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Session-Based Recommendation Model: Run the recommender with an increased training set
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Cross-Validation Mode: Perform five-fold cross-validation