This project applies a Random Forest Classifier to predict whether a student will Pass or Fail based on their features
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Aug 20, 2025 - Jupyter Notebook
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feature-importance-analysis
Here are 10 public repositories matching this topic...
Customer Churn Prediction System using XGBoost Regressor, built on Telecom Industry dataset
customer-retention churn-prediction random-forest-classifier xgboost-regression feature-importance-analysis
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Jun 17, 2025 - Jupyter Notebook
An Analysis and Machine Learning model to understand employee retention and predict churn as part of the Google Advanced Data Analytics Certificate Capstone Project.
python machine-learning cross-validation eda xgboost decision-trees auc-roc-score feature-importance-analysis
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Mar 25, 2025 - Jupyter Notebook
U-M MADS: Milestone Project | ML-powered system that detects and classifies racial bias in news articles using supervised and unsupervised learning techniques, to provide comprehensive bias analysis.
clustering exploratory-data-analysis dimensionality-reduction topic-modeling data-preprocessing feature-engineering sensitivity-analysis hyperparameter-tuning model-evaluation model-development text-preprocessing failure-analysis tradeoff-analysis feature-importance-analysis
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Jul 20, 2024 - Jupyter Notebook
Develops 2 machine learning models that predict which customers are likely to leave the service, and to identify the most influential factors contributing to churn.
logistic-regression confusion-matrix classification-report random-forest-classifier customer-churn-prediction roc-auc-curve feature-importance-analysis
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Aug 5, 2025 - Jupyter Notebook
VOC-based plant phenotyping using PTR-ToF-MS data from tomato genotypes under different treatments.
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Jun 24, 2025 - Jupyter Notebook
Predict telecom customer churn using machine learning models with Python, scikit-learn, and pandas.
python data-science machine-learning scikit-learn pandas classification gridsearchcv feature-importance-analysis
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Aug 26, 2025 - Jupyter Notebook
scraping premier League 2021-2022 season Data and predicting the result (Win/ Lose) as a classification problem using Gradient Boost and random Forest.
performance-metrics gradient-boosting random-forest-classifier google-colab xgboost-classifier feature-importance-analysis
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Aug 27, 2025 - Jupyter Notebook
Machine learning for predicting negative cardiac outcomes in patients with atrial fibrillation (AF)
deep-learning survival-analysis shap explainability shapley-value cox-proportional-hazard feature-importance-analysis
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Mar 17, 2025 - Python
This project compares the effects of Ridge (L2) and Lasso (L1) regression models on clinical data.
ridge-regression hyperparameter-tuning l2-regularization lasso-regression regression-analysis feature-importance l1-regularization parameter-optimization regularization-techniques diabetes-dataset feature-importance-analysis
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Feb 21, 2025 - Jupyter Notebook
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