Group-5---Code-Case-Seminar

Python and R code used for Case Seminar 2024

The structure and order of this zip-file is as follows:

README file
Code for creation of the dataset (Code Dataset Creation.py) - Python code used for importing the data and all data preprocessing techniques (feature engineering, external data, missing values, aggregation, etc)
Code for the four models we used: Logistic Regression (Python), XGBoost (Python), RSF (folder with both R and Python files), LSTM (folder with Python files)
Code for generating plots from our results (Python)

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
Code Dataset Creation.py		Code Dataset Creation.py
Code LSTM - main_hyperparam.py		Code LSTM - main_hyperparam.py
Code LSTM - main_preprocess.py		Code LSTM - main_preprocess.py
Code LSTM - main_test.py		Code LSTM - main_test.py
Code LSTM - main_train.py		Code LSTM - main_train.py
Code LSTM - metrics.py		Code LSTM - metrics.py
Code LSTM - model.py		Code LSTM - model.py
Code Logistic Regression.py		Code Logistic Regression.py
Code RSF - Model Taining, Tuning, and Evaluating.R		Code RSF - Model Taining, Tuning, and Evaluating.R
Code RSF - Stochastic Shapley Values 1 (R).R		Code RSF - Stochastic Shapley Values 1 (R).R
Code RSF - Stochastic Shapley Values 2 (Python).py		Code RSF - Stochastic Shapley Values 2 (Python).py
Code RSF - Time to Event Variable.py		Code RSF - Time to Event Variable.py
Code XGBoost.py		Code XGBoost.py
README.md		README.md

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