This code aims to predict the risk of Cardiovascular Disease based on personal lifestyle factors. The dataset, sourced from the Behavioral Risk Factor Surveillance System (BRFSS) - a leading health survey in the U.S., has been refined from 304 variables down to 19 crucial lifestyle-related factors linked to cardiovascular diseases.
The code initiates by importing necessary libraries for data analysis, modeling, and plotting. It then reads the dataset and checks for duplicates.
The target variable is set, and the data is categorized into numerical and categorical columns.
The code then delves into multivariate analysis for both numerical and categorical data. Preprocessing steps are carried out, including setting the target variable, splitting the data, and creating pipelines.
A fit and train function is defined, and various pipelines and models are set up. Finally, predictions are obtained from the models.
This code emphasizes the importance of understanding the underlying patterns within the data, which could potentially lead to better diagnostic tools or interventions for cardiovascular diseases in the future.
This script is open-source and licensed under the MIT License. For more details, check the LICENSE file.