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Cardio-Vascular-Disease-analysis ❤️ 🏥 EDA

Прогнозирование вероятности сердечно-сосудистых заболеваний у пациентов по 12 признакам.

Prediction CVD in patients. This is my small pet-project about cardiovascular disease (CVD) in patients of different ages using 12 features. “Cardio” is the target feature.

Preliminarily, I cleaned the data and got rid of outliers. Then I made some visualizations and tested a few hypotheses. Further I compared 3 classifiers: RandomForest, XGBoost and LightGBM without tuning. XGBoost showed the best result. In the end, I made visualization with showing the most important features for the each of above classifiers. Also, there is a Power BI dashboard.

Click on "Open in Colab" below to see DETAILED conclusions and code: Open In Google Colab

PowerBI dash with some conclusions based on data: cardio-analysis

Your feedback is welcome to me. 🙌