In this project, I will use two machine learning models, Random Forest and Logistic Regression, to predict heart disease. This is a simple model where I use all available variables to make the prediction. I won’t delve too deeply into the problem beyond the estimation part. In reality, establishing causal inference requires more subject expertise and looking beyond the data for analytics. However, the goal today is to demonstrate and practice running these two machine learning models.

Running a simple regression on the eammi2 data.

Referencia entre las unidades de primer nivel a las de segundo nivel, generales y comunitarios. Con la información podemos determinar la cobertura de servicio y la población que atiende.