Kindly assist in comprehensive data analysis$($including plots and graphs$)$ in python that tries to meet objectives to develop and demonstrate a predictive model using machine learning techniques that identifies individuals at higher risk of TB infection and quantify and compare the stability of machine learning models across different districts$($geographic regions$)$ and explore consistency of identified risk factors contributing to the models. Using Supervised learning $($classification algorithms like logistic regression, decision trees, SVM$),$ feature selection, cross$-$validation as well as model evaluation $($e$.$g$.,$ performance metrics like accuracy, precision, recall$),$ statistical tests for comparing models and identifying consistent risk factors. with dataset containing the following features;