H1N1-Vaccination-Prediction

The prediction of H1N1 vaccination involves using survey data to develop a predictive model that can determine whether individuals received the H1N1 vaccine or not. This typically entails analyzing various features or variables from the survey, such as demographic information, previous vaccination history, health-related factors, and attitudes towards vaccines. Machine learning algorithms such as Linear Regression, Decision Trees, SVM, KNN, Boosting etc are employed to build a model that classifies individuals as either vaccinated or not vaccinated for H1N1. This model is valuable for public health organizations in identifying factors that influence vaccination rates and for targeting interventions to improve vaccine uptake.