- 📈 Application : Visual Analytics for ML
- 📕 Report : Case Study Report
Development of a predictive model for the "display" variable using Machine Learning techniques by transforming all continuous variables into categorical for modeling.
📌 Descriptive analysis of qualitative and quantitative variables, and their transformation for analysis.
📉 Use of MCA to reduce data dimensionality, identify principal components, and interpret results.
- Decision Tree: Classification with specific parameters and a confusion matrix to assess performance.
- Random Forest: Application of random forest, parameter tuning, and classification results.
- Logistic Regression: Prediction using logistic regression, including error rates and accuracy metrics.
📊 Comparative analysis of three machine learning models: Decision Tree, Random Forest, and Logistic Regression.
📏 Evaluation of model performance based on precision and sensitivity.
🚀 Let's make data-driven decisions!