GitHub - leabrodyheine/ML-Kaggle-Cirrhosis-Data: This project showcases skills in machine learning, data preprocessing, and model evaluation using Python libraries such as scikit-learn, XGBoost, and Optuna. It involves implementing various machine learning models, handling imbalanced data, and employing imputation techniques to enhance model performance for predicting cirrhosis outcomes.

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This project showcases skills in machine learning, data preprocessing, and model evaluation using Python libraries such as scikit-learn, XGBoost, and Optuna. It involves implementing various machine learning models, handling imbalanced data, and employing imputation techniques to enhance model performance for predicting cirrhosis outcomes.

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Name		Name	Last commit message	Last commit date
Latest commit History 132 Commits
Group20_submission.csv		Group20_submission.csv
ID5059_P2_Final.ipynb		ID5059_P2_Final.ipynb
Imputation Method.ipynb		Imputation Method.ipynb
baseline_predictions.csv		baseline_predictions.csv
impuation models- kaggle results.pdf		impuation models- kaggle results.pdf
imputed_predictions1.csv		imputed_predictions1.csv
imputed_predictions2.csv		imputed_predictions2.csv
imputed_predictions3.csv		imputed_predictions3.csv
requirements.txt		requirements.txt
sample_submission.csv		sample_submission.csv
submission.csv		submission.csv
test.csv		test.csv
train.csv		train.csv